Author: "LRIT" - Searchworks@Jio Institute Digital Library Search Results

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235 results on '"LRIT"'

1. Arabic stems are being built in a database utilising an automated process.

Author: Laabidi, Abderrahman, primary, Yousfi, Abdellah, additional, Lrit, Said Iazzi, additional, and Aouragh, Si Lhoussain, additional
Published: 2023
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2. Encephalomyelitis Associated with Anti-myelin Oligodendrocyte Glycoprotein Antibodies and Adenovirus.

Author: Melamed, Shirel Barnea, Ganelin-Cohen, Esther, Bulkowstein, Yarden, Rootman, Mika Shapira, and Krause, lrit
Published: 2023

3. A novel method for image categorization based on histogram oriented gradient and support vector machine

Author: Mohammed Rziza Lrit, Mohammed El Hassouni, Mohammed Reda Guedira, and Abderrahim El Qadi
Subjects: 010304 chemical physics, Computer science, business.industry, Feature extraction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Wavelet transform, Pattern recognition, 02 engineering and technology, 01 natural sciences, Haar wavelet, Image (mathematics), Support vector machine, ComputingMethodologies_PATTERNRECOGNITION, Transformation (function), Categorization, Histogram, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, business
Abstract: In this paper, we introduce a new method for categorisation natural image based on different techniques. Concerning the color and texture, we made a pre-treatment to convert the database images on to the gray-scale and the Haar wavelet transformation. For this, we use the Oriented Gradient Histogram (HOG) for each sub-band to extract these image features. We have used a proper classification based on the support vector machine (SVM) to recognize these images. The result part and experience applied on a Corel database that is known in natural images shows a better performance of the proposed system based on accuracy and speed compared to other CBIR methods.
Published: 2017
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4. A novel method for image categorization based on histogram oriented gradient and support vector machine

Author: Guedira, Mohammed Reda, primary, Qadi, Abderrahim El, additional, Lrit, Mohammed Rziza, additional, and Hassouni, Mohammed El, additional
Published: 2017
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5. Recognition of adult video by combining skin detection features with motion information

Author: Sanaa Elfkihi Lrit, Driss Aboutajdine, Abdelilah Jilbab, and Hajar Bouirouga
Subjects: Artificial neural network, Pixel, Computer science, business.industry, Bayesian probability, Feature extraction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Motion detection, Pattern recognition, Motion (physics), Color model, Skin color, Computer vision, Artificial intelligence, business, ComputingMethodologies_COMPUTERGRAPHICS
Abstract: This paper presents a novel approach for video adult detection using skin detection features with motion information. The goal of combining skin-color and motion information is to select the appropriate color model that allows verifying pixels under different lighting conditions and other variations. Then, the output videos are classified by neural network. The simulation shows that this system achieved 90% of the true rate.
Published: 2011
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6. Growth hormone releasing activity by intranasal administration of a synthetic hexapeptide (hexarelin)

Author: Zvi Laron, B. Klinger, Vincent Lengerts, Patrick Wuthrich, Lrit Gil‐Ad, Jenny Frenkel, Francois Boutignon, Ernesto Lubin, and Romano Deghenghi
Subjects: Male, medicine.medical_specialty, Adolescent, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Microgram, Thyrotropin, Peptide hormone, Growth hormone, Route of administration, Endocrinology, Internal medicine, medicine, Humans, Child, Growth Substances, Administration, Intranasal, Growth Disorders, Chemotherapy, business.industry, Hormones, Growth hormone-releasing peptide, Child, Preschool, Growth Hormone, Injections, Intravenous, Female, Nasal administration, business, Oligopeptides, Hormone
Abstract: OBJECTIVE Hexarelin is a new synthetic growth hormone releasing peptide. We have tested the efficacy of intranasal (i.n.) administration of hexarelin to stimulate plasma GH and have compared this to the intravenous (i.v.) administration of the peptide. PATIENTS Ten children with familial short stature (FSS) aged 5.5-15.5 years and two known GH deficient patients aged 24 and 28 years without GH treatment. METHODS All 12 subjects were submitted to i.v. (1 microgram/kg) and i.n. (20 micrograms/kg) hexarelin tests with a one-week interval between tests. Blood samples for GH, TSH, fT4 and T3 were obtained at 0, 15, 30, 60, 90 and 120 minutes. The hormone determinations were made by standard radio-immunoassays (RIA). RESULTS Both the i.n. and i.v. administration of hexarelin induced a large GH response, the mean (+/- SD) being 72.2 +/- 35.5 mU/l for the i.n. test and 79.6 +/- 53.0 mU/l for the i.v. test. The peak GH in the i.v. test occurred at 15-30 minutes and in the i.n. test between 30 and 60 minutes. The GH deficient patients showed no GH response in either test. Plasma TSH decreased in the FSS children from a mean (+/- SD) of 1.0 +/- 0.26 to 0.64 +/- 0.2 mU/l (P < 0.005) during the i.n. test and from 1.0 +/- 0.3 to 0.7 +/- 0.3 mU/l (P < 0.05) during the i.v. test. In the isolated GH deficient patient, plasma TSH decreased from 1.06 +/- 0.38 mU/l to 0.86 +/- 0.17 during the i.v. test and from 1.60 +/- 0.01 to 1.11 +/- 0.06 mU/l during the i.n. test. There were no significant changes in plasma fT4 or T3 in any of the tests. CONCLUSIONS The synthetic hexapeptide hexarelin is a potent pituitary GH stimulator when administered intranasally. The GH response was similar to that observed after intravenous hexarelin. Simultaneously, there was a significant decrease in plasma TSH but the concentrations remained in the normal range. These findings appear to be of theoretical and practical relevance to the investigation and management of short children.
Published: 1994
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7. Recognition of adult video by combining skin detection features with motion information

Author: Bouirouga, Hajar, primary, Lrit, Sanaa Elfkihi, additional, Jilbab, Abdelilah, additional, and Aboutajdine, Driss, additional
Published: 2011
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8. Growth hormone releasing activity by intranasal administration of a synthetic hexapeptide (hexarelin)

Author: Laron, Zvi, primary, Frenkel, Jenny, additional, Gil-Ad, lrit, additional, Klinger, Beatrice, additional, Lubin, Ernesto, additional, Wuthrich, Patrick, additional, Boutignon, François, additional, Lengerts, Vincent, additional, and Deghenghi, Romano, additional
Published: 1994
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9. Bridging the Semantic Gap for Texture-based Image Retrieval and Navigation

Author: Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT) ; Univ. of Mohammed V, Laboratoire d'Informatique de Nantes Atlantique (LINA) ; CNRS - Université de Nantes - École Nationale Supérieure des Mines - Nantes, Idrissi, Najlae, Martinez, José, Aboutajdine, D., Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT) ; Univ. of Mohammed V, Laboratoire d'Informatique de Nantes Atlantique (LINA) ; CNRS - Université de Nantes - École Nationale Supérieure des Mines - Nantes, Idrissi, Najlae, Martinez, José, and Aboutajdine, D.
Abstract: International audience

10. Rocket Fire Pierces, but Does Not Burst, the Bubble Encircling Tel Aviv.

Author: KERSHNER, ISABEL and Garshowit, lrit Pazner
Subjects: TEL Aviv (Israel)
Published: 2021

11. Right and Left Skeptical Of Netanyahu Proposal.

Author: KERSHNER, ISABEL and Garshowitz, lrit Pazner
Abstract: The article focuses on Prime Minister Benjamin Netanyahu who called for destruction of militant group Hamas in 2009 campaign and mentions sincerity of Netanyahu about election-eve vow to annex the Jordan River valley.
Published: 2019

12. A Novel Texture Descriptor: Circular Parts Local Binary Pattern

Author: Mohammed Rziza, Johan Debayle, Ibtissam Al Saidi, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Département Procédés de Mise en oeuvre des Milieux Granulaires (PMMG-ENSMSE), Centre Sciences des Processus Industriels et Naturels (SPIN-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire Georges Friedel (LGF-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), and Université Mohammed V - LRIT-CNRST URAC 29
Subjects: Medicine (General), Texture classification, Acoustics and Ultrasonics, Local binary patterns, Computer science, Materials Science (miscellaneous), General Mathematics, Feature extraction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Texture (music), R5-920, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, QA1-939, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, Radiology, Nuclear Medicine and imaging, Local binary pattern (LBP), Instrumentation, Pixel, business.industry, Texture Descriptor, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Support vector machine, Computer Science::Computer Vision and Pattern Recognition, Signal Processing, Pattern recognition (psychology), Computer Vision and Pattern Recognition, Artificial intelligence, business, Mathematics, Biotechnology, Curse of dimensionality
Abstract: Local Binary Pattern (LBP) are considered as a classical descriptor for texture analysis, it has mostly been used in pattern recognition and computer vision applications. However, the LBP gets information from a restricted number of local neighbors which is not enough to describe texture information, and the other descriptors that get a large number of local neighbors suffer from a large dimensionality and consume much time. In this regard, we propose a novel descriptor for texture classification known as Circular Parts Local Binary Pattern (CPLBP) which is designed to enhance LBP by extending the area of neighborhood from one to a region of neighbors using polar coordinates that permit to capture more discriminating relationships that exists amongst the pixels in the local neighborhood which increase efficiency in extracting features. Firstly, the circle is divided into regions with a specific radius and angle. After that, we calculate the average gray-level value of each part. Finally, the value of the center pixel is compared with these average values. The relevance of the proposed idea is validate in databases Outex 10 and 12. A complete evaluation on benchmark data sets reveals CPLBP's high performance. CPLBP generates the score of 99.95 with SVM classification.
Published: 2021
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13. A novel texture descriptor: Homogeneous Rotated Local Binary Pattern (HRLBP)

Author: Johan Debayle, Mohammed Rziza, Ibtissam Al Saidi, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Département Procédés de Mise en oeuvre des Milieux Granulaires (PMMG-ENSMSE), Centre Sciences des Processus Industriels et Naturels (SPIN-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire Georges Friedel (LGF-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Mines Saint-Etienne, and Université Mohammed V - LRIT-CNRST URAC 29
Subjects: Pixel, business.industry, Local binary patterns, Texture Descriptor, Homogeneity (statistics), Feature extraction, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, Thresholding, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, Artificial intelligence, Invariant (mathematics), business, Rotation (mathematics), Mathematics
Abstract: Invariant rotation in the application of texture classification is generally beneficial due to the material: camera or auto rotation, which can affect objects captured by arbitrary angles. This letter, introduce a new, efficient rotation invariant descriptor for texture analysis appointed Homogeneous Rotated Local Binary Pattern (HRLBP). The goal of this novel method is to take more account of the intrinsic characteristics of the images in rotation changing by using the incidence of homogeneity tolerance h provide from General Adaptive Neighborhood (GAN). A significant features are generated from HRLBP by thresholding the center and each neighbor pixels with an homogeneity tolerance value which help to get more efficient and discriminating features for rotation variation further multi-scale changing owing to use a variation of the parameter of homogeneity tolerance h and radius R. The experiments are evaluated using two publicly available texture database OTC10, furthermore, HRLBP shown a high performance in classification accuracy for problem of rotation variation.
Published: 2021

14. Automatic detection of Moroccan coastal upwelling zones using sea surface temperature images

Author: Hussein Yahia, Khalid Minaoui, Ayoub Tamim, Salma El Fellah, Khalid Daoudi, Mohamed El Ansari, Driss Aboutajdine, Abderrahman Atillah, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Ibn Zohr [Agadir], Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), and Université Mohammed V de Rabat [Agdal] (UM5)
Subjects: 010504 meteorology & atmospheric sciences, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, Fuzzy logic, Sea surface temperature images, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Cluster (physics), Segmentation, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Cluster validity indices, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Upwelling, business.industry, Fuzzy c-means clustering, k-means clustering, Pattern recognition, Filter (signal processing), Region-growing algorithm, Sea surface temperature, General Earth and Planetary Sciences, Satellite, Artificial intelligence, business, Geology
Abstract: International audience; An efficient unsupervised method is developed for automatic segmentation of the area covered by upwelling waters in the coastal ocean of Morocco using the Sea Surface Temperature (SST) satellite images. The proposed approach first uses the two popular unsupervised clustering techniques, k-means and fuzzy c-means (FCM), to provide different possible classifications to each SST image. Then several cluster validity indices are combined in order to determine the optimal number of clusters, followed by a cluster fusion scheme, which merges consecutive clusters to produce a first segmentation of upwelling area. The region-growing algorithm is then used to filter noisy residuals and to extract the final upwelling region. The performance of our algorithm is compared to a popular algorithm used to detect upwelling regions and is validated by an oceanographer over a database of 92 SST images covering each week of the years 2006 and 2007. The results show that our proposed method outperforms the latter algorithm, in terms of segmentation accuracy and computational efficiency.
Published: 2018
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15. A Robust Blind 3-D Mesh Watermarking Technique Based on SCS Quantization and Mesh Saliency for Copyright Protection

Author: Mohammed El Hassouni, Hocine Cherifi, Aladine Chetouani, Mohamed El Haziti, Mohamed Hamidi, Chetouani, Aladine, LRIT Associated Unit to the CNRST-URAC n◦ 29, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME), Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Université Mohammed V de Rabat [Agdal], Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: FOS: Computer and information sciences, Computer Science - Cryptography and Security, Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Quantization (signal processing), Data_MISCELLANEOUS, 020207 software engineering, Watermark, 02 engineering and technology, Graphics (cs.GR), Computer Science - Graphics, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Computer engineering, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Polygon mesh, Vertex normal, Quantization (image processing), Digital watermarking, Cryptography and Security (cs.CR), ComputingMilieux_MISCELLANEOUS, Smoothing
Abstract: Due to the recent demand of 3-D meshes in a wide range of applications such as video games, medical imaging, film special effect making, computer-aided design (CAD), among others, the necessity of implementing 3-D mesh watermarking schemes aiming to protect copyright has increased in the last decade. Nowadays, the majority of robust 3-D watermarking approaches have mainly focused on the robustness against attacks while the imperceptibility of these techniques is still a serious challenge. In this context, a blind robust 3-D mesh watermarking method based on mesh saliency and scalar Costa scheme (SCS) for Copyright protection is proposed. The watermark is embedded by quantifying the vertex norms of the 3-D mesh by SCS scheme using the vertex normal norms as synchronizing primitives. The choice of these vertices is based on 3-D mesh saliency to achieve watermark robustness while ensuring high imperceptibility. The experimental results show that in comparison with the alternative methods, the proposed work can achieve a high imperceptibility performance while ensuring a good robustness against several common attacks including similarity transformations, noise addition, quantization, smoothing, elements reordering, etc., Comment: 10 pages, 11 figures, 5th International Conference on Mobile, Secure and Programmable Networking (MSPN'2019)
Published: 2019

16. Blind Robust 3-D Mesh Watermarking Based on Mesh Saliency and QIM Quantization for Copyright Protection

Author: Aladine Chetouani, Mohamed El Haziti, and Hocine Cherifi, Mohammed El Hassouni, Mohamed Hamidi, LRIT Associated Unit to the CNRST-URAC n◦ 29, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME), Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Université Mohammed V de Rabat [Agdal], Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Chetouani, Aladine, Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Subjects: business.industry, Computer science, Watermark robustness, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Data_MISCELLANEOUS, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, Quantization index modulation, Watermark, 02 engineering and technology, Vertex (geometry), [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Quantization (image processing), Digital watermarking, Smoothing, ComputingMilieux_MISCELLANEOUS
Abstract: International audience; Due to the recent demand of 3-D models in several applications like medical imaging, video games, among others, the necessity of implementing 3-D mesh watermarking schemes aiming to protect copyright has increased considerably. The majority of robust 3-D watermark-ing techniques have essentially focused on the robustness against attacks while the imperceptibility of these techniques is still a real issue. In this context, a blind robust 3-D mesh watermarking method based on mesh saliency and Quantization Index Modulation (QIM) for Copyright protection is proposed. The watermark is embedded by quantifying the vertex norms of the 3-D mesh using QIM scheme since it offers a good robustness-capacity tradeoff. The choice of the vertices is adjusted by the mesh saliency to achieve watermark robustness and to avoid visual distortions. The experimental results show the high imperceptibility of the proposed scheme while ensuring a good robustness against a wide range of attacks including additive noise, similarity transformations, smoothing , quantization, etc.
Published: 2019
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17. 3D visual saliency and convolutional neural network for blind mesh quality assessment

Author: Longin Jan Latecki, Mohammed El Hassouni, Hocine Cherifi, Aladine Chetouani, Ilyass Abouelaziz, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME), Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), LRIT, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V-University of Mohammed V, Laboratoire d'Informatique de Bourgogne [Dijon] (LIB), and Université de Bourgogne (UB)
Subjects: 0209 industrial biotechnology, Computer science, business.industry, media_common.quotation_subject, Emphasis (telecommunications), Pattern recognition, 02 engineering and technology, Filter (signal processing), Convolutional neural network, 020901 industrial engineering & automation, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Artificial Intelligence, Distortion, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Quality (business), Polygon mesh, Saliency map, Artificial intelligence, business, Feature learning, Software, media_common
Abstract: International audience; A number of full reference and reduced reference methods have been proposed in order to estimate the perceived visual quality of 3D meshes. However, in most practical situations, there is a limited access to the information related to the reference and the distortion type. For these reasons, the development of a no-reference mesh visual quality (MVQ) approach is a critical issue, and more emphasis needs to be devoted to blind methods. In this work, we propose a no-reference convolutional neural network (CNN) framework to estimate the perceived visual quality of 3D meshes. The method is called SCNN-BMQA (3D visual saliency and CNN for blind mesh quality assessment). The main contribution is the usage of a CNN and 3D visual saliency to estimate the perceived visual quality of distorted meshes. To do so, the CNN architecture is fed by small patches selected carefully according to their level of saliency. First, the visual saliency of the 3D mesh is computed. Afterward, we render 2D projections from the 3D mesh and its corresponding 3D saliency map. Then the obtained views are split into 2D small patches that pass through a saliency filter in order to select the most relevant patches. Finally, a CNN is used for the feature learning and the quality score estimation. Extensive experiments are conducted on four prominent MVQ assessment databases, including several tests to study the effect of the CNN parameters, the effect of visual saliency and comparison with existing methods. Results show that the trained CNN achieves good rates in terms of correlation with human judgment and outperforms the most effective state-of-the-art methods. Keywords Mesh visual quality assessment Á Mean opinion score Á Mesh visual saliency Á Convolutional neural network
Published: 2019
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18. Hybrid blind robust image watermarking technique based on DFT-DCT and Arnold transform

Author: Mohammed El Hassouni, Mohamed El Haziti, Hocine Cherifi, Mohamed Hamidi, LRIT Associated Unit to the CNRST-URAC n◦ 29, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Mohammed V de Rabat [Agdal], Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Faculté des Lettres et Sciences humaines, and FLSH Saïs, Fès, Maroc
Subjects: FOS: Computer and information sciences, Computer Science - Cryptography and Security, Computer Networks and Communications, Computer science, Multiple Watermarking, 02 engineering and technology, Discrete Fourier transform, Image (mathematics), Digital image, Discrete Fourier transform (DFT), Scheme, Robustness (computer science), Quantization, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, Discrete cosine transform, Hybrid method, [INFO]Computer Science [cs], Digital watermarking, Discrete cosine transform (DCT), Distance, Image watermarking, 020207 software engineering, Watermark, Multimedia (cs.MM), Hardware and Architecture, Medical Images, Embedding, 020201 artificial intelligence & image processing, Arnold transform, Wavelet Domain, Svd, Cryptography and Security (cs.CR), Algorithm, Copyright protection, Software, Computer Science - Multimedia
Abstract: In this paper, a robust blind image watermarking method is proposed for copyright protection of digital images. This hybrid method relies on combining two well-known transforms that are the discrete Fourier transform (DFT) and the discrete cosine transform (DCT). The motivation behind this combination is to enhance the imperceptibility and the robustness. The imperceptibility requirement is achieved by using magnitudes of DFT coefficients while the robustness improvement is ensured by applying DCT to the DFT coefficients magnitude. The watermark is embedded by modifying the coefficients of the middle band of the DCT using a secret key. The security of the proposed method is enhanced by applying Arnold transform (AT) to the watermark before embedding. Experiments were conducted on natural and textured images. Results show that, compared with state-of-the-art methods, the proposed method is robust to a wide range of attacks while preserving high imperceptibility., 34 page, 17 figures, published in Multimedia Tools and Applications Springer, 2018
Published: 2018
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19. Efficient Dense Disparity Map Reconstruction using Sparse Measurements

Author: Mohammed Rziza, Aouatif Amine, Cédric Demonceaux, Oussama Zeglazi, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), VIsion pour la roBOTique [VIBOT CNRS ERL 6000] (VIBOT), Centre National de la Recherche Scientifique (CNRS)-Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Laboratoire de Recherche Informatique et Télécommunications ( LRIT ), Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ), Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, European Masters in Computer Vision and Robotics [VIBOT] ( VIBOT ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), and Demonceaux, Cédric
Subjects: Vertical Median Filter, Pixel, business.industry, Computer science, Scanline Propagation, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Stereo matching, Boundary (topology), [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Scan line, Stereo Matching, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Sampling (signal processing), Computer Science::Computer Vision and Pattern Recognition, Outlier, Median filter, Artificial intelligence, Superpixel, Cluster analysis, business
Abstract: International audience; In this paper, we propose a new stereo matching algorithm able to reconstruct efficiently a dense disparity maps from few sparse disparity measurements. The algorithm is initialized by sampling the reference image using the Simple Linear Iterative Clustering (SLIC) superpixel method. Then, a sparse disparity map is generated only for the obtained boundary pixels. The reconstruction of the entire disparity map is obtained through the scanline propagation method. Outliers were effectively removed using an adaptive vertical median filter. Experimental results were conducted on the standard and the new Middlebury datasets show that the proposed method produces high-quality dense disparity results.
Published: 2018

20. Centrality in Networks with Overlapping Communities

Author: Ghalmane, Z., El Hassouni, Mohammed, Cherifi, Chantal, Cherifi, Hocine, DISP, HAL, LRIT, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V-University of Mohammed V, Décision et Information pour les Systèmes de Production (DISP), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: [INFO]Computer Science [cs], [INFO] Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2018

21. k-Truss Decomposition for Modular Centrality

Author: Mohammed El Hassouni, Zakariya Ghalmane, Chantal Cherifi, Hocine Cherifi, DISP, HAL, LRIT, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V-University of Mohammed V, Décision et Information pour les Systèmes de Production (DISP), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)
Subjects: Theoretical computer science, Computer science, Property (programming), business.industry, Node (networking), Community structure, Complex network, Modular design, [INFO] Computer Science [cs], 01 natural sciences, 010305 fluids & plasmas, Ranking, Component (UML), 0103 physical sciences, [INFO]Computer Science [cs], 010306 general physics, business, Centrality, ComputingMilieux_MISCELLANEOUS
Abstract: There is currently much interest in identifying influential spreaders in complex networks due to many applications concerned, such as controlling the outbreak of epidemics and conducting advertisements for commercial products, and so on. A plethora of centrality measures have been proposed over the years based on the topological properties of networks. However, most of these classical centrality measures fail to select the most influential nodes in networks with a modular structure despite that it is an omnipresent property in real-world networks. Few authors have introduced centrality measures tailored to networks with community structure. In a recent work, we have shown that, in this case, the centrality of a node should be represented by a two-dimensional vector. The first component quantifies the local influence of the node in its community, while the second component quantifies the global influence of the node on the communities which it is linked to. In order to compute the so-called modular centrality, one needs to know the community structure of the network. Unfortunately, in most cases, it is unknown and a community detection algorithm must be used. The majority of these algorithms are computationally intensive and sometimes they are inappropriate for large networks. In this paper, a community detection method based on the k-truss decomposition is used. Thanks to its nice structural and computational properties, it is well-adapted to large networks. Furthermore, we present a new ranking measure based on the weighted combination of both components of the modular centrality. Using the Susceptible-Infected-Recovered (SIR) model in epidemic spreading simulations, we show that substantial improvements can be gained in order to identify the influential spreaders with significantly less computational cost and complexity.
Published: 2018

22. Target Recognition in Radar Images Using Weighted Statistical Dictionary-Based Sparse Representation

Author: Abdelmalek Toumi, Ali Khenchaf, Ayoub Karine, Mohammed El Hassouni, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Pôle STIC_REMS, École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne), Lab-STICC_ENSTAB_MOM_PIM, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Lab-STICC_ENSTAB_CID_TOMS, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)
Subjects: Synthetic aperture radar, Computer science, 0211 other engineering and technologies, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Wavelet transforms, Wavelet, Radar imaging, 0202 electrical engineering, electronic engineering, information engineering, Target recognition, Training, Computer vision, Electrical and Electronic Engineering, Complex wavelet transform, 021101 geological & geomatics engineering, business.industry, Wavelet transform, Pattern recognition, Statistical model, Sparse approximation, Geotechnical Engineering and Engineering Geology, Inverse synthetic aperture radar, [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, Feature (computer vision), Dictionaries, 020201 artificial intelligence & image processing, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; In this letter, we present a novel generic approach for radar automatic target recognition in either inverse synthetic aperture radar (ISAR) or synthetic aperture radar (SAR) images. For this purpose, the radar image is described by a statistical modeling in the complex wavelet domain. Thus, the radar image is transformed into a complex wavelet domain using the dual-tree complex wavelet transform. Afterward, the magnitudes of the complex sub-bands are modeled by Weibull or Gamma distributions. The estimated parameters of these models are stacked together to create a statistical dictionary in training step. For the recognition task, we use the weighted sparse representation-based classification method that captures the linearity and locality information of image features. In this context, we propose to use the Kullback-Leibler divergence between the parametric statistical models of training and test sets in order to assign a weight for each training sample. Experiments conducted on both ISAR and SAR images' databases demonstrate that the proposed approach leads to an improvement in the recognition rate.
Published: 2017
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23. A robust blind 3-D mesh watermarking based on wavelet transform for copyright protection

Author: Driss Aboutajdine, Mohamed El Haziti, Mohamed Hamidi, Hocine Cherifi, LRIT Associated Unit to the CNRST-URAC n◦ 29, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Mohammed V de Rabat [Agdal], Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Subjects: FOS: Computer and information sciences, 0209 industrial biotechnology, Computer science, video watermarking, 02 engineering and technology, Watermarking, image watermarking, 020901 industrial engineering & automation, Wavelet, copy protection, vectors, Robustness (computer science), Computer Science::Multimedia, 0202 electrical engineering, electronic engineering, information engineering, wavelet coefficient vectors, Controlled Indexing, Computer vision, Polygon mesh, Quantization (image processing), Robustness, Digital watermarking, ComputingMilieux_MISCELLANEOUS, Computer Science::Cryptography and Security, Quantization (signal), digital watermarking, business.industry, copyright, edge normal norms, Wavelet transform, unauthorized users, Watermark, Three-dimensional meshes, Multimedia (cs.MM), mesh generation, wavelet transforms, synchronizing primitives, 3D semiregular meshes, Solid modeling, robust blind 3D mesh watermarking, 020201 artificial intelligence & image processing, Artificial intelligence, Laplacian smoothing, business, Copyright protection, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Computer Science - Multimedia, image resolution, Digital images
Abstract: Nowadays, three-dimensional meshes have been extensively used in several applications such as, industrial, medical, computer-aided design (CAD) and entertainment due to the processing capability improvement of computers and the development of the network infrastructure. Unfortunately, like digital images and videos, 3-D meshes can be easily modified, duplicated and redistributed by unauthorized users. Digital watermarking came up while trying to solve this problem. In this paper, we propose a blind robust watermarking scheme for three-dimensional semiregular meshes for Copyright protection. The watermark is embedded by modifying the norm of the wavelet coefficient vectors associated with the lowest resolution level using the edge normal norms as synchronizing primitives. The experimental results show that in comparison with alternative 3-D mesh watermarking approaches, the proposed method can resist to a wide range of common attacks, such as similarity transformations including translation, rotation, uniform scaling and their combination, noise addition, Laplacian smoothing, quantization, while preserving high imperceptibility., Comment: 6 pages, 3 figures, International Conference on Advanced Technologies for Signal and Image Processing (ATSIP'2017)
Published: 2017
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24. An overview of the CATE algorithms for real-time pitch determination

Author: El Hassan Ibn Elhaj, Fadoua Bahja, Joseph Di Martino, Driss Aboutajdine, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Analysis, perception and recognition of speech (PAROLE), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Institut National des Postes et Télécommunications (INPT), Institut National des Postes et Telecommunications, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), Institut National des Postes et Télécommunications [Rabat] (INPT), and Université Mohammed V de Rabat [Agdal] (UM5)
Subjects: Majority rule, Decision error, Computer science, business.industry, Speech recognition, Frame (networking), Autocorrelation, Pattern recognition, Pitch detection algorithm, Pitch period, Circular autocorrelation, Reduction (complexity), Majority vote, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Signal Processing, Cepstrum, Voice, Artificial intelligence, Electrical and Electronic Engineering, business, Real-time, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithm
Abstract: International audience; In this paper, we present a recent algorithm for pitch detection based on an implicit circular autocorrelation of the glottal excitation signal. This algorithm operates in real time without the use of any post-processing technique. This article focuses on the correction of the pitch contours estimated and on the reduction in classification errors in speech signals using simple voicing decision techniques. To evaluate the performance of our algorithms, we used the Bagshaw and Keele databases. We show in this study that the sum of the percentage of the unvoiced errors and the percentage of the voiced errors, for the male Bagshaw corpus, reaches a very good score of 14.67. For the female corpus, our results are also competitive compared to other algorithms using the same database. Concerning the Keele database, we succeed to obtain very good gross pitch error, voicing decision error and F0 frame error rates, respectively, 0.44, 0.65 and 1.55 % in the whole corpus.
Published: 2013
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25. Classification parcimonieuse pour l’aide à la reconnaissance de cibles radar

Author: ayoub karine, Abdelmalek Toumi, Ali Khenchaf, Mohammed El Hassouni, Billon-Coat, Annick, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), LRIT, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V-University of Mohammed V, Lab-STICC_ENSTAB_CID_TOMS, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Pôle STIC_REMS, École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne), Lab-STICC_ENSTAB_MOM_PIM, Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, DTCWT, SIFT, [SPI.ELEC] Engineering Sciences [physics]/Electromagnetism, image ISAR, Reconnaissance automatique des cibles, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; Dans le présent papier, nous proposons l’étude et l’application d’une nouvelle approche pour l’aide à la reconnaissance automatique de cibles (ATR, pour Automatic Target Recognition) à partir des images à synthèse d’ouverture inverse (ISAR, pour Inverse Synthetic Aperture Radar). Cette approche est composée de deux phases principales. Dans la première phase, nous utilisons deux méthodes statistiques pour extraire les caractéristiques discriminants à partir des images ISAR. Nous nous intéressons dans ce travail aux deux descripteurs multiéchelles issus des deux méthodes SIFT (Scale-Invariant Feature Transform) et la décomposition en ondelettes complexes DT-CWT (Dual-Tree Complex Wavelet Transform) qui sont calculées disjointement. Ensuite, nous modélisons séparément les descripteurs issus des deux méthodes précédentes (SIFT et DTCWT) par la loi Gamma. Les paramètres statistiques estimés sont utilisés pour la deuxième phase dédiée à la classification. Dans cette deuxième phase, une classification parcimonieuse (SRC, pour Sparse Representation-based Classification) est proposée. Afin d’évaluer et valider notre approche, nous avons eu recours aux données réelles d’images issues d’une chambre anéchoïque. Les résultats expérimentaux montrent que l’approche proposée peut atteindre un taux de reconnaissance élevé et dépasse largement l’utilisation du même descripteur avec le classifieur machine à vecteurs de support (SVM, pour Support Vector Machine).
Published: 2017

26. ACCURATE DENSE STEREO MATCHING FOR ROAD SCENES

Author: Cédric Demonceaux, Mohammed Rziza, Oussama Zeglazi, Aouatif Amine, Demonceaux, Cédric, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Recherche Informatique et Télécommunications ( LRIT ), Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ) -Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ), Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), and Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: Computer science, business.industry, [ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO], [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO], 0211 other engineering and technologies, Stereo matching, Cross Comparison Census, 02 engineering and technology, Stereo vision, Cross based aggregation, Stereopsis, Census Transform, Robustness (computer science), 0202 electrical engineering, electronic engineering, information engineering, Radiometry, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, 021101 geological & geomatics engineering
Abstract: International audience; Stereo matching task is the core of applications linked to the intelligent vehicles. In this paper, we present a new variant function of the Census Transform (CT) which is more robust against radiometric changes in real road scenes. We demonstrate that the proposed cost function outperforms the conventional cost functions using the KITTI benchmark. The cost aggregation method is also updated for taking into account the edge information. This enables to improve significantly the aggregated costs especially within homogenous regions. The Winner-Takes-All (WTA) strategy is used to compute disparity values. To further eliminate the remainder matching ambiguities , a post-processing step is performed. Experiments were conducted on the new Middlebury 2 dataset, as well as on the real road traffic scenes of the KITTI database. Obtained disparity results have demonstrated that the proposed method is promising.
Published: 2017

27. Ex-Aide Wins Office in 60-to-59 Vote.

Author: KINGSLEY, PATRICK, PÉREZ-PEÑA, RICHARD, Garshowitz, lrit Pazner, Noveck, Myra, Rasgon, Adam, Kershner, Isabel, and Sobelman, Gabby
Subjects: *VOTING
Abstract: The article reports on how Naftali Bennett, a former aide of Israeli Prime Minister Benjamin Netanyahu, succeeded in creating a coalition government and replaced Netanyahu as prime minister in June 2021. Newly appointed Foreign Minister Yair Lapid will replace Bennett after two years as part of their deal. Also cited are the allegations against Netanyahu, including undermining the rule of law by remaining in his position while being tried for corruption.
Published: 2021

28. An Image Segmentation Algorithm based on Community Detection

Author: Mohammed El Hassouni, Youssef Mourchid, Hocine Cherifi, LRIT, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V-University of Mohammed V, Departement des Sciences et Techniques de la Communication (DESTEC), Université Mohammed V de Rabat [Agdal], Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Cherifi Hocine, Gaito Sabrina, Quattrociocchi Walter, Sala Alessandra, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), Departement des Sciences et Techniques de la Communication ( DESTEC ), Université Mohammed 5 Agdal, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: [ INFO ] Computer Science [cs], Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Scale-space segmentation, 02 engineering and technology, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Minimum spanning tree-based segmentation, Image texture, 0202 electrical engineering, electronic engineering, information engineering, community detection, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Segmentation, [INFO]Computer Science [cs], [ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI], modularity, Image segmentation, Segmentation-based object categorization, business.industry, [ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO], Pattern recognition, complex networks, Histogram of oriented gradients, Region growing, 020201 artificial intelligence & image processing, Artificial intelligence, business
Abstract: International audience; With the recent advances in complex networks, image segmentation becomes one of the most appropriate application areas. In this context, we propose in this paper a new perspective of image segmentation by applying two efficient community detection algorithms. By considering regions as communities, these methods can give an over-segmented image that has many small regions. So, the proposed algorithms are improved to automatically merge those neighboring regions agglomerative to achieve the highest modularity/stability. To produce sizable regions and detect homogeneous communities, we use the combination of a feature based on the Histogram of Oriented Gradients of the image, and feature based on color to characterize the similarity of two regions. By constructing the similarity matrix in an adaptive manner, we avoid the problem of the over-segmentation. We evaluate the proposed algorithms for Berkeley Segmentation Dataset, and we show that our experimental results can outperform other segmentation methods in terms of accuracy and can achieve much better segmentation results.
Published: 2016
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29. Aircraft recognition using a statistical model and sparserepresentation

Author: Ali Khenchaf, Mohammed El Hassouni, Abdelmalek Toumi, Ayoub Karine, Lab-STICC_ENSTAB_MOM_PIM, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Pôle STIC_REMS, École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne), Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Lab-STICC_ENSTAB_CID_TOMS, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), and University of Mohammed V
Subjects: business.industry, Computer science, 0211 other engineering and technologies, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Scale-invariant feature transform, Pattern recognition, Statistical model, 02 engineering and technology, Sparse approximation, Inverse synthetic aperture radar, Automatic target recognition, Computer Science::Computer Vision and Pattern Recognition, 0202 electrical engineering, electronic engineering, information engineering, Feature (machine learning), 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, Complex wavelet transform, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 021101 geological & geomatics engineering
Abstract: International audience; This paper presents a novel approach for automatic targetrecognition (ATR) using inverse synthetic aperture radar(ISAR) images. This proposed approach is mainly com-posed of two steps. In the rst step, we adopt a statisti-cal method to compute a novel target template from fea-ture descriptors. The proposed template is achieved bycombining the Gamma statistical parameters of the bothdual-tree complex wavelet transform (DT-CWT) coecientsand the scale-invariant feature transform (SIFT) descrip-tor. In order to validate the proposed target template,we achieve in the second step the recognition task usinga sparse representation-based classication (SRC) method.The performance of the proposed approach has been success-fully veried using ISAR images reconstructed from anechoicchamber. The experimental results show that the proposedmethod can achieve a high average accuracy and is signi-cantly superior to the well-known SVM classier.
Published: 2016
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30. VISUAL SALIENT SIFT KEYPOINTS DESCRIPTORS FOR AUTOMATIC TARGETRECOGNITION

Author: Karine, Ayoub, Toumi, Abdelmalek, Khenchaf, Ali, Hassouni, Mohammed El, Lab-STICC_ENSTAB_MOM_PIM, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Pôle STIC_REMS, École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne), Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Lab-STICC_ENSTAB_CID_TOMS, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), and University of Mohammed V
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, classification, inverse synthetic aperture radar, SIFT, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, visual attention model, Automatic target recognition, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; This paper addresses the problem of automatic target recognition(ATR) using inverse synthetic aperture radar (ISAR) images.In this context, we propose a novel approach for featureextraction to describe precisely an aircraft target from ISARimages. In our approach, a visual attention model is adoptedto separate the salient regions from the background. Afterthat, the scale invariant feature transform (SIFT) method isused to extract the keypoints and their descriptors. Then, alocal salient feature is built by considering only the keypointslocated in the salient region. For the classification step, thesupport vector machines (SVM) classifier is adopted. To validatethe proposed approach, ISAR images database whichwas collected from anechoic chamber is used.
Published: 2016

31. A phase-based framework for optical flow estimation on omnidirectional images

Author: Amina Radgui, Mohammed Rziza, Driss Aboutajdine, Brahim Alibouch, Cédric Demonceaux, LRIT, Laboratoire de Recherche Informatique et Télécommunications ( LRIT ), Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ) -Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ), Institut National de Postes et Télécommunications [Rabat] ( INPT ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Institut National des Postes et Télécommunications [Rabat] (INPT), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, Computer science, Optical flow, 02 engineering and technology, Component velocity, [SPI]Engineering Sciences [physics], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Robustness (computer science), [ INFO.INFO-TI ] Computer Science [cs]/Image Processing, 0202 electrical engineering, electronic engineering, information engineering, [ SPI ] Engineering Sciences [physics], Computer vision, Multimedia information systems, Electrical and Electronic Engineering, Omnidirectional antenna, Large field of view, business.industry, 020206 networking & telecommunications, Spherical wavelets, [ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR], Omnidirectional images, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Optical flow estimation, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Signal Processing, [SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic, 020201 artificial intelligence & image processing, Omnidirectional vision, Artificial intelligence, [ SPI.OPTI ] Engineering Sciences [physics]/Optics / Photonic, business, Phase-based methods
Abstract: International audience; Over the past few years, omnidirectional vision has become an important area of research because omnidirectional cameras offer a large field of view compared with conventional perspectives cameras. However, omnidirectional images contain important distortions, and classical optical flow estimations are thus not appropriate. In this paper, we propose to estimate optical flow on omnidirectional images using a phase-based method which proved its robustness and its accuracy on the perspective images. We will adapt different treatments in order to take into account the nature of omnidirectional images.
Published: 2016
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32. No-Reference 3D Mesh Quality Assessment Based on Dihedral Angles Model and Support Vector Regression

Author: Mohammed El Hassouni, Ilyass Abouelaziz, Hocine Cherifi, Laboratoire de Recherche Informatique et Télécommunications ( LRIT ), Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: Gamma distribution, [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, [ INFO ] Computer Science [cs], Computer science, 02 engineering and technology, computer.software_genre, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Quality (physics), [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Visual masking, Distortion, 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], Polygon mesh, [ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI], No-reference mesh quality assessment, Visual masking effect, 020207 software engineering, Support vector machine, Support vector regression, Quality Score, Human visual system model, Dihedral angles, 020201 artificial intelligence & image processing, Data mining, Algorithm, computer
Abstract: International audience; 3D meshes are subject to various visual distortions during their transmission and geometrical processing. Several works have tried to evaluate the visual quality using either full reference or reduced reference approaches. However, these approaches require the presence of the reference mesh which is not available in such practical situations. In this paper, the main contribution lies in the design of a computational method to automatically predict the perceived mesh quality without reference and without knowing beforehand the distortion type. Following the no-reference (NR) quality assessment principle, the proposed method focuses only on the distorted mesh. Specifically, the dihedral angles are firstly computed as a surface roughness indexes and so a structural information descriptors. Then, a visual masking modulation is applied to this angles according to the main characteristics of the human visual system. The well known statistical Gamma model is used to fit the dihedral angles distribution. Finally, the estimated parameters of the model are learned to the support vector regression (SVR) in order to predict the quality score. Experimental results demonstrate the highly competitive performance of the proposed no-reference method relative to the most influential methods for mesh quality assessment.
Published: 2016
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33. Detection of Moroccan coastal upwelling in SST images using the Expectation-Maximization

Author: Driss Aboutajdine, Khalid Daoudi, Khalid Minaoui, Ayoub Tamim, Abderrahman Atillah, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), and This work is funded by the French-Moroccan research pro- gram Volubilis (MA/11/256) and the project n◦MPI 12/2010.
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Upwelling, Meteorology, Dunn index, Davies-Bouldin index, Area opening, Image segmentation, Expectation-Maximisation, Sea surface temperature, Geography, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Robustness (computer science), Expectation–maximization algorithm, Sea Surface Temperature, Segmentation, Satellite, Submarine pipeline, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract: International audience; This paper proposes an unsupervised algorithm for automatic detection and segmentation of upwelling region in Moroccan Atlantic coast using the Sea Surface Temperature (SST) satellite images. This has been done by exploring the Expectation-Maximization algorithm. The good number of clus- ters that best reproduces the shape of upwelling areas is selected by using the two popular Davies-Bouldin and Dunn indices. Area opening technique is developed that is used to remove and discarded the residuals noise in offshore waters not belonging to the upwelling region. The complete system has been validated by an oceanographer using a database of 30 SST images of the year 2007, demonstrating its capability and robustness for precise detection of Moroccan coastal upwelling.
Published: 2015
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34. Reduced reference 3D mesh quality assessment based on statistical models

Author: Mounir Omari, Mohammed El Hassouni, Hocine Cherifi, Ilyass Abouelaziz, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Sponsor(s):Kasetsart University in Bangkok, LE2I (Laboratoire Electronique, Image et Informatique), University of Bourgogne, UKNOW, Center of Excellence for Unified Knowledge and Language Engineering at Kasetsart University., IEEE Computer Society, IEEE Computer Society Technical & Conference Activities Board, University of Milan, Dipanda, A, Yetongnon, K, Chbeir, R, Laboratoire de Recherche Informatique et Télécommunications ( LRIT ), Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: Gamma distribution, [ INFO ] Computer Science [cs], Kullback–Leibler divergence, Kullback-Leibler divergence, statistical modeling, Context (language use), 02 engineering and technology, human visual system, Databases, [SPI]Engineering Sciences [physics], [ SPI ] Engineering Sciences [physics], 0202 electrical engineering, electronic engineering, information engineering, computational geometry, Polygon mesh, [INFO]Computer Science [cs], Divergence (statistics), Mathematics, ComputingMethodologies_COMPUTERGRAPHICS, Visualization, business.industry, 020207 software engineering, Statistical model, Pattern recognition, statistical distributions, Distortion, Geometry processing, 3D triangle mesh, [ SPI.TRON ] Engineering Sciences [physics]/Electronics, image processing, [SPI.TRON]Engineering Sciences [physics]/Electronics, Human visual system model, Metric (mathematics), Solid modeling, Three-dimensional displays, 020201 artificial intelligence & image processing, Distortion measurement, Weibull distribution, Artificial intelligence, business, objective metric, Quality assessment
Abstract: International audience; During their geometry processing and transmission 3D meshes are subject to various visual processing operations like compression, watermarking, remeshing, noise addition and so forth. In this context it is indispensable to evaluate the quality of the distorted mesh, we talk here about the mesh visual quality (MVQ) assessment. Several works have tried to evaluate the MVQ using simple geometric measures, However this metrics do not correlate well with the subjective score since they fail to reflect the perceived quality. In this paper we propose a new objective metric to evaluate the visual quality between a mesh with a perfect quality called reference mesh and its distorted version. The proposed metric uses a chosen statistical distribution to extract parameters of two random variable sets, the first set is the dihedral angles related to the reference mesh, while the second set is the dihedral angles related to the distorted mesh. The perceptual distance between two meshes is computed as the Kullback-Leibler divergence between the two sets of variables. Experimental results from two subjective databases (LIRIS masking database and LIRIS/EPFL general purpose database) and comparisons with seven objective metrics cited in the state-of-the-art demonstrate the efficacy of the proposed metric in terms of the correlation to the mean opinion scores across these databases.
Published: 2015
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35. Visual contact with catadioptric cameras

Author: Driss Aboutajdine, Sanaa Elfkihi, Cédric Demonceaux, Fatima Zahra Benamar, El Mustapha Mouaddib, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Modélisation, Information & Systèmes ( MIS ), Université de Picardie Jules Verne ( UPJV ), Laboratoire de Recherche Informatique et Télécommunications ( LRIT ), Université Mohammed 5 Agdal-Centre National de la Recherche Scientifique et Technologique ( CNRST ), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Modélisation, Information et Systèmes - UR UPJV 4290 (MIS), Université de Picardie Jules Verne (UPJV), Laboratoire de Recherche Informatique et Télécommunications (LRIT), and Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST)
Subjects: 0209 industrial biotechnology, Computer science, General Mathematics, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Optical flow, 02 engineering and technology, Catadioptric system, 020901 industrial engineering & automation, Omnidirectional camera, Depth map, 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Computer vision, ComputingMilieux_MISCELLANEOUS, Pixel, business.industry, Perspective (graphical), [ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO], Mobile robot, Real image, Computer Science Applications, Control and Systems Engineering, Obstacle, 020201 artificial intelligence & image processing, Artificial intelligence, business, Software
Abstract: Time to contact or time to collision (TTC) is utmost important information for animals as well as for mobile robots because it enables them to avoid obstacles; it is a convenient way to analyze the surrounding environment. The problem of TTC estimation is largely discussed in perspective images. Although a lot of works have shown the interest of omnidirectional camera for robotic applications such as localization, motion, monitoring, few works use omnidirectional images to compute the TTC. In this paper, we show that TTC can be also estimated on catadioptric images. We present two approaches for TTC estimation using directly or indirectly the optical flow based on de-rotation strategy. The first, called “gradient based TTC”, is simple, fast and it does not need an explicit estimation of the optical flow. Nevertheless, this method cannot provide a TTC on each pixel, valid only for para-catadioptric sensors and requires an initial segmentation of the obstacle. The second method, called “TTC map estimation based on optical flow”, estimates TTC on each point on the image and provides the depth map of the environment for any obstacle in any direction and is valid for all central catadioptric sensors. Some results and comparisons in synthetic and real images will be given.
Published: 2015
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36. An Efficient Tool for Automatic Delimitation of Moroccan Coastal Upwelling Using SST Images

Author: Ayoub Tamim, Abderrahman Atillah, Hussein Yahia, Khalid Minaoui, Khalid Daoudi, Driss Aboutajdine, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), LRIT Associated Unit to the CNRST-URAC n◦ 29, Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Université Mohammed V de Rabat [Agdal] (UM5), and CORDI-S grant
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, unsu-pervised classification, —Sea surface temperature image, Image segmentation, Region-growing algorithm, Geotechnical Engineering and Engineering Geology, Otsu's method, symbols.namesake, Sea surface temperature, upwelling, Oceanography, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Climatology, Moroccan atlantique coast, symbols, Upwelling, Satellite, Segmentation, Submarine pipeline, Electrical and Electronic Engineering, Cluster analysis, Geology
Abstract: International audience; An unsupervised classification method is developed for the coarse segmentation of Moroccan coastal upwelling using the Sea Surface Temperature (SST) satellite images. The algorithm is started with the generation of c-partitioned labeled image using Otsu's method for the purpose of finding regions of homogenous temperatures. Then two well-known validity indices are used to select the c-partition which best reproduce the shape of upwelling area. A region-growing algorithm is developed that is used to remove the noisy structures in the offshore waters not belonging to the upwelling area. The algorithm is used to provide a seasonal variability of upwelling activity in the southern Moroccan Atlantic coast using 70 SST images of the years 2007 and 2008. The performance of the proposed methodology has been validated by an oceanographer, showing its effectiveness for automatic delimitation of Moroccan upwelling region.
Published: 2014

37. Upwelling Detection in SST Images Using Fuzzy Clustering with Adaptive Cluster Merging

Author: Tamim, Ayoub, Minaoui, Khalid, Daoudi, Khalid, Atillah, Abderrahman, Yahia, Hussein, Aboutajdine, Driss, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), LRIT Associated Unit to the CNRST-URAC n◦ 29, Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), and Université Mohammed V de Rabat [Agdal] (UM5)
Subjects: AVHRR, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, ComputingMethodologies_PATTERNRECOGNITION, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Sea Surface Temperature, Index Terms—Upwelling, Clustering, Adaptive cluster merging
Abstract: International audience; The current paper explores the applicability of the Fuzzy c-means (FCM) clustering, using an adaptive cluster merging, for the problem of detecting the Moroccan coastal upwelling areas in Sea Surface Temperature (SST) Satellite images. The process is started with the application of FCM clustering method to the SST image with a sufficiently large number of clusters for the purpose of labelling the original SST image, which constitute the input of the proposed approach. Then, the number of clusters is reduced successively by merging clusters that are similar with respect to an adaptive threshold criterion. The algorithm is applied and validated using the visual inspection carried out by an oceanographer over a database of 30 SST images, covering the southern Moroccan atlantic coast of the year 2007. The proposed methodology is shown to be promising and reliable for a majority of images used in this study.
Published: 2014

38. A simple tool for automatic extraction of Moroccan coastal upwelling from Sea Surface Temperature images

Author: Ayoub Tamim, Hussein Yahia, Driss Aboutajdine, Abderrahman Atillah, Khalid Daoudi, Khalid Minaoui, Mohammed Faouzi Smiej, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), LRIT Associated Unit to the CNRST-URAC n◦ 29, Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Université Mohammed V de Rabat [Agdal] (UM5), Utilisation scientifique des images du satellites MSG acquises en temps réel (MSG-ATR), Centre National de la Recherche Scientifique (CNRS), Centre Royal de Télédétection Spatiale, IEEE, and IEEE Morocco Section
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation, Sea surface temperature, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Advanced very-high-resolution radiometer, Computer science, Climatology, Upwelling, Extraction (military), Satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; This work aims at automatically identify and ex- tract the region covered by the upwelling waters in the costal ocean of Morocco using the well known region-growing segmen- tation algorithm. The later consists in coarse segmentation of upwelling area which characterized by cold and usually nutrient- rich water near the coast. The complete system has been validated by an oceanographer over a database of 30 Sea Surface Tem- perature (SST) satellite images of the year 2007 obtained from Advanced Very High Resolution Radiometer (AVHRR) sensor onboard NOAA-18 satellite serie, demonstrating its capability and effectiveness to reproduce the shape of upwelling area.
Published: 2014
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39. Dynamic Facial Expression Generation on Hilbert Hypersphere With Conditional Wasserstein Generative Adversarial Nets

Author: Stefano Berretti, Mohammed Daoudi, Anis Kacem, Lahoucine Ballihi, Naima Otberdout, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, University Mohammed V, Rabat, Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT), Dipartimento di Sistemi e Informatica (DSI), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Université de Florence, Université Mohammed V de Rabat [Agdal] (UM5), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Università degli Studi di Firenze = University of Florence (UniFI), and ANR-16-IDEX-0004,ULNE,ULNE(2016)
Subjects: FOS: Computer and information sciences, Computer science, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Motion (geometry), Facial Landmarks, 02 engineering and technology, Riemannian geometry, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Image (mathematics), Conditional manifold-valued Wasserstein Generative Adversarial Networks, Motion, symbols.namesake, Artificial Intelligence, Facial expression generation, 0202 electrical engineering, electronic engineering, information engineering, ComputingMethodologies_COMPUTERGRAPHICS, Facial expression, business.industry, Applied Mathematics, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, Hypersphere, Facial Expression, ComputingMethodologies_PATTERNRECOGNITION, Distribution (mathematics), Computational Theory and Mathematics, Face, symbols, 020201 artificial intelligence & image processing, Neural Networks, Computer, Computer Vision and Pattern Recognition, Artificial intelligence, business, Algorithms, Software, Generative grammar
Abstract: International audience; In this work, we propose a novel approach for generating videos of the six basic facial expressions given a neutral face image. We propose to exploit the face geometry by modeling the facial landmarks motion as curves encoded as points on a hypersphere. By proposing a conditional version of manifold-valued Wasserstein generative adversarial network (GAN) for motion generation on the hypersphere, we learn the distribution of facial expression dynamics of different classes, from which we synthesize new facial expression motions. The resulting motions can be transformed to sequences of landmarks and then to images sequences by editing the texture information using another conditional Generative Adversarial Network. To the best of our knowledge, this is the first work that explores manifold-valued representations with GAN to address the problem of dynamic facial expression generation. We evaluate our proposed approach both quantitatively and qualitatively on two public datasets; Oulu-CASIA and MUG Facial Expression. Our experimental results demonstrate the effectiveness of our approach in generating realistic videos with continuous motion, realistic appearance and identity preservation. We also show the efficiency of our framework for dynamic facial expressions generation, dynamic facial expression transfer and data augmentation for training improved emotion recognition models.
Published: 2022
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40. Estimation des cartes du temps de collision (TTC) basée sur le flot optique en vision para-catadioptrique

Author: Cédric Demonceaux, Driss Aboutajdine, Sanaa El Fkihi, El Mustapha Mouaddib, Fatima Zahra Benamar, Laboratoire MIS, Université de Picardie Jules Verne, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), University of Mohammed V, RIITM, ENSAIS, Université Mohammed V, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Université de Picardie Jules Verne (UPJV), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Subjects: [ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO], [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Electrical and Electronic Engineering
Abstract: International audience; RÉSUMÉ. Cet article s'intéresse à l'estimation du temps de collision d'un robot mobile muni d'une caméra catadioptrique. Ce type de caméra est très utile en robotique car il permet d'ob-tenir un champ de vue panoramique à chaque instant. Le temps de collision a été largement étudié dans le cas des caméras perspectives. Cependant, ces méthodes ne sont pas directement applicables et nécessitent d'être adaptées, à cause des distorsions des images obtenues par les caméras omnidirectionnelles. Dans ce travail, nous proposons de tirer parti du flot optique cal-culé sur les images omnidirectionnelles pour en déduire le temps de collision (TTC) entre le robot et l'obstacle. Nous verrons que la double projection d'un point 3D sur le miroir puis sur le plan caméra aboutit à une nouvelle formulation du TTC pour les caméras catadioptriques. Cette formulation nous permet de connaître à chaque instant et sur chaque pixel de l'image le TTC à partir du flot optique en ce point. Notre approche est validée sur des données de syn-thèse et des expérimentations réelles. Enfin, nous montrons que ce calcul permet de détecter les obstacles situés dans l'axe du mouvement du robot.
Published: 2014
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41. Performance Index for Tensor Polyadic Decompositions

Author: Comon, P., Minaoui khalid, Rouijel, A., Aboutajdine, D., GIPSA - Communication Information and Complex Systems (GIPSA-CICS), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, Eurasip, European Project: 320594,EC:FP7:ERC,ERC-2012-ADG_20120216,DECODA(2013), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), and Université Mohammed V de Rabat [Agdal] (UM5)
Subjects: Canonical polyadic, Identification, Parafac, Performance, Array, 020206 networking & telecommunications, Candecomp, 02 engineering and technology, Blind, Tensor, CP, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Source separation, Data mining, Coherence, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; It is proposed to isolate the computation of the scaling matrix in CP tensor decompositions. This has two implications. First, the conditioning of the problem shows up explicitly, and could be controlled via a constraint on the so-called coherences. Second, a performance measure concerning only the factor matrices can be exactly calculated, and does not present the optimistic bias of the minimal error generally utilized in the literature. In fact, for tensors of order $d$, it suffices to solve a degree-2 polynomial system in $d$ variables. We subsequently give an explicit solution when d=3.
Published: 2013

42. A SIMPLE AND EFFICIENT APPROACH FOR COARSE SEGMENTATION OF MOROCCAN COASTAL UPWELLING

Author: Tamim, A., Minaoui khalid, Daoudi, K., Yahia, H., Atillah, A., Smiej, M. F., Aboutajdine, D., LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), LRIT Associated Unit to the CNRST-URAC n◦ 29, Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Utilisation scientifique des images du satellites MSG acquises en temps réel (MSG-ATR), Centre National de la Recherche Scientifique (CNRS), Centre Royal de Télédétection Spatiale, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), and Université Mohammed V de Rabat [Agdal] (UM5)
Subjects: ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Upwelling, sea surface temperature, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, unsupervised classification, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, segmentation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; In this work, we aim to develop a simple and fast algorithm using conventional methods in images segmentation for the automatic detection and extraction of upwelling areas, in the coastal region of Morocco, from the sea surface temperature (SST) satellite images. Our approach is based on the evalua- tion and comparison between two unsupervised classification methods, Otsu and Fuzzy C-means, and explores the appli- cability of these methods to our classification problem. The latter consists in coarse detection of the main thermal front that separates coastal cold upwelling waters from the remain- ing ocean waters. The algorithm has been applied and val- idated by an oceanographer over a database of 66 SST im- ages corresponding to southern Moroccan coastal upwelling of the years 2004, 2005, 2007 and 2009. The results indicate that the proposed algorithm revealed is promising and reli- able on different upwelling scenarios and for a wide variety of oceanographic conditions.
Published: 2013

43. Gradient-based time to contact on paracatadioptric camera

Author: S. El Fkihi, Driss Aboutajdine, Cédric Demonceaux, El Mustapha Mouaddib, Fatima Zahra Benamar, Modélisation, Information & Systèmes ( MIS ), Université de Picardie Jules Verne ( UPJV ), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), University of Mohammed V, RIITM, ENSAIS, Université Mohammed V, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Modélisation, Information et Systèmes - UR UPJV 4290 (MIS), Université de Picardie Jules Verne (UPJV), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, and Demonceaux, Cédric
Subjects: 0209 industrial biotechnology, [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Computer science, mobile robotic, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Optical flow, Time to contact, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, 02 engineering and technology, obstacle avoidance, Catadioptric system, 020901 industrial engineering & automation, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, omnidirectional vision, Obstacle avoidance, 0202 electrical engineering, electronic engineering, information engineering, collision detection, Collision detection, Computer vision, Image sensor, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Feature detection (computer vision), Orientation (computer vision), business.industry, Perspective (graphical), Mobile robot, 020201 artificial intelligence & image processing, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; The problem of time to contact or time to collision (TTC) estimation is largely discussed in perspective images. However, a few works have dealt with images of catadioptric sensors despite of their utility in robotics applications. The objective of this paper is to develop a novel model for estimating TTC with catadioptric images relative to a planar surface, and to demonstrate that TTC can be estimated only with derivative brightness and image coordinates. This model, called "gradient based time to contact", does not need high processing such as explicit estimation of optical flow and feature detection/or tracking. The proposed method allows to estimate TTC and gives additional information about the orientation of planar surface. It was tested on simulated and real datasets.
Published: 2013
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44. A New Image Distortion Measure Based on Natural Scene Statistics Modeling

Author: Abdelkaher Ait Abdelouahad, Mohammed El Hassouni, Hocine Cherifi, Driss Aboutajdine, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, LRIT, University of Mohammed V-University of Mohammed V, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Information Resources Management Association, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020206 networking & telecommunications, 020201 artificial intelligence & image processing, 02 engineering and technology, [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Abstract: International audience; In the field of Image Quality Assessment (IQA), this paper examines a Reduced Reference (RRIQA) measure based on the bi-dimensional empirical mode decomposition. The proposed measure belongs to Natural Scene Statistics (NSS) modeling approaches. First, the reference image is decomposed into Intrinsic Mode Functions (IMF); the authors then use the Generalized Gaussian Density (GGD) to model IMF coefficients distribution. At the receiver side, the same number of IMF is computed on the distorted image, and then the quality assessment is done by fitting error between the IMF coefficients histogram of the distorted image and the GGD estimate of IMF coefficients of the reference image, using the Kullback Leibler Divergence (KLD). In addition, the authors propose a new Support Vector Machine-based classification approach to evaluate the performances of the proposed measure instead of the logistic function-based regression. Experiments were conducted on the LIVE dataset.
Published: 2013
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45. Estimation des Cartes du Temps de Collision (TTC) en Vision Para-catadioptrique

Author: Benamar, Fatima Zahra, Demonceaux, Cédric, El Fkihi, Sanaa, Mouaddib, E., Aboutajdine, Driss, Modélisation, Information & Systèmes ( MIS ), Université de Picardie Jules Verne ( UPJV ), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), University of Mohammed V, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), RIITM, ENSAIS, Université Mohammed V, Demonceaux, Cédric, Modélisation, Information et Systèmes - UR UPJV 4290 (MIS), Université de Picardie Jules Verne (UPJV), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], vision omnidirectionnelle, évitement d'obstacle, [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO], [ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO], Temps de collision, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], TTC
Abstract: National audience; Le temps de contact ou le temps de collision (TTC) est une information importante pour la navigation et l'évitement d'obtacles. Son estimation a largement été étudiée dans le cas des caméras perspectives. Par contre, très peu de travaux ont été effectués sur ce sujet pour les caméras catadioptriques, alors qu'elles sont très utiles, notamment, en navigation des robots mobiles. L'objectif de cet article, est de proposer un nouveau modèle d'estimation du TTC pour les caméras paracatadioptriques basé sur le flot optique, en adaptant celui développé pour les caméras perspectives. Le calcul du TTC en chaque pixel permet d'obtenir la carte des temps de collision. Nous avons validé ce modèle sur des images de synthèse et sur des séquences réelles.
Published: 2013

46. Energy Efficiency of MIMO Cooperative Networks with Energy Harvesting Sensor Nodes

Author: Youssef Fakhri, Samir Saoudi, Driss Aboutajdine, Said El Abdellaoui, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, Equipe Réseaux et Télécommunication (RT), Département d'Informatique [Kénitra], Faculté des Sciences [Kenitra], Université Ibn Tofaïl (UIT)-Université Ibn Tofaïl (UIT)-Faculté des Sciences [Kenitra], Université Ibn Tofaïl (UIT)-Université Ibn Tofaïl (UIT), Lab-STICC_TB_CACS_COM, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Département Signal et Communications (SC), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Centre de la Recherche Scientifique et Technologique au Maroc (CRST) (CRST), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), Equipe Réseaux et Télécommunication ( RT ), Faculté des Sciences [Kenitra]-Université Ibn Tofaïl ( UIT ) -Faculté des Sciences [Kenitra]-Université Ibn Tofaïl ( UIT ), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance ( Lab-STICC ), École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ) -École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ), Département Signal et Communications ( SC ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], and Centre de la Recherche Scientifique et Technologique au Maroc (CRST) ( CRST )
Subjects: Power management, Computer science, MIMO, Cooperation Communication, 02 engineering and technology, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, law.invention, 0203 mechanical engineering, Relay, law, Hardware_GENERAL, 0202 electrical engineering, electronic engineering, information engineering, Energy-Efficiency, business.industry, Node (networking), 020206 networking & telecommunications, 020302 automobile design & engineering, Optimal Power Allocation, Amplify-and-Forward, Transmission (telecommunications), business, Telecommunications, MIMO Cooperative, Energy harvesting, Wireless sensor network, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Computer network, Efficient energy use
Abstract: International audience; This paper addresses the maximizing network lifetime problem in wireless sensor networks (WSNs) taking into account the total Symbol Error rate (SER) at destination. Therefore, efficient power management is needed for extend network lifetime. Our approach consists to provide the optimal transmission power using the orthogonal multiple access channels between each sensor. In order to deeply study the properties of our approach, firstly, the simple case is considered; the information sensed by the source node passes by a single relay before reaching the destination node. Secondly, global case is studied; the information passes by several relays. We consider, in the previous both cases, that the batteries are nonrechargeable. Thirdly, we spread our work the case where the batteries are rechargeable with unlimited storage capacity. In all three cases, we suppose that Maximum Ratio Combining (MRC) is used as a detector, and Amplify and Forward (AF) as a relaying strategy. Simulation results show the viability of our approach which the network lifetime is extended of more than 70.72%when the batteries are non rechargeable and 100.51% when the batteries are rechargeable in comparison with other traditional method.
Published: 2013

47. Reduced reference image quality assessment based on statistics in empirical mode decomposition domain

Author: Driss Aboutajdine, Abdelkaher Ait Abdelouahad, Mohammed El Hassouni, Hocine Cherifi, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), University of Mohammed V, LRIT, University of Mohammed V-University of Mohammed V, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Subjects: Kullback–Leibler divergence, Kullback-Leibler divergence, Image quality, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020206 networking & telecommunications, 02 engineering and technology, Reduced reference image quality assessment, [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Measure (mathematics), Support vector machine, Intrinsic mode function, Histogram, Generalized Gaussian density, Signal Processing, Metric (mathematics), Statistics, 0202 electrical engineering, electronic engineering, information engineering, Range (statistics), 020201 artificial intelligence & image processing, Electrical and Electronic Engineering, Divergence (statistics), Mathematics
Abstract: International audience; This paper deals with the image quality assessment (IQA) task using a natural image statistics approach. A reduced reference (RRIQA) measure based on the bidimensional empirical mode decomposition is introduced. First, we decompose both, reference and distorted images, into intrinsic mode functions (IMF) and then we use the generalized Gaussian density (GGD) to model IMF coefficients of the reference image. Finally, we measure the impairment of a distorted image by fitting error between the IMF coefficients histogram of the distorted image and the estimated IMF coefficients distribution of the reference image, using the Kullback-Leibler divergence (KLD). Furthermore, to predict the quality, we propose a new support vector machine-based (SVM) classification approach as an alternative to logistic function-based regression. In order to validate the proposed measure, three benchmark datasets are involved in our experiments. Results demonstrate that the proposed metric compare favorably with alternative solutions for a wide range of degradation encountered in practical situations.
Published: 2012
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48. Time to Contact Estimation on Paracatadioptric Cameras

Author: Benamar, Fatima Zahra, Demonceaux, Cédric, El Fkihi, Sanaa, Mouaddib, El Mustapha, Aboutajdine, Driss, Modélisation, Information et Systèmes - UR UPJV 4290 (MIS), Université de Picardie Jules Verne (UPJV), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, RIITM, ENSAIS, Université Mohammed V, Modélisation, Information & Systèmes ( MIS ), Université de Picardie Jules Verne ( UPJV ), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] ( GSCM-LRIT ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), and Demonceaux, Cédric
Subjects: [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO], [ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO], ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]
Abstract: International audience; Time to contact or time to collision (TTC) is the time available to a robot before reaching an object. In this paper, we propose to estimate this time using a catadioptric camera embedded on th erobot. Indeed, whereas a lot of works have shown the utility of this kind of cameras in robotic applications (monitoring, locali- sation, motion,...), a few works deal with the problem of time to contact estimation on it. Thus, in this paper, we propose a new work which allows to define and to estimate the TTC on catadioptric camera. This method will be validated on simulated and real data.
Published: 2012

49. Texture analysis using dual tree m-band and Rényi entropy. Application to osteoporosis diagnosis on bone radiographs

Author: El Hassani, Ahmed Salmi, El Hassouni, Mohammed, Houam, Lotfi, Rziza, Mohamed, Lespessailles, Eric, Jennane, Rachid, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), University of Mohammed V, LRIT, University of Mohammed V-University of Mohammed V, Département Images, Robotique, Automatique et Signal [Orléans] (IRAUS), Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME), Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Imagerie Multimodale Multiéchelle et Modélisation du Tissu Osseux et articulaire (I3MTO), and Université d'Orléans (UO)
Subjects: Dual Tree M-Band, Rényi Divergence, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Osteoporosis, ACT-Inter, Texture, Bone, Rényi Entropy, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; In this paper, we propose a new method based on texture analysis for trabecular bone disease diagnosis. For this purpose, we present a working model based on a preprocessing step followed by a projection on a 1D oriented axis at a defined angle. First, the dual-tree transform M-band is applied on the 1D obtained signal. Then, the Rényi based information measure is computed on sub-bands coefficients in order to characterize the anisotropy which is strongly present in our application related to bone radiograph characterization. Finally, the Wilcoxon test is used on the Rényi entropies obtained for each subband and the K nearest neighborhoods classifier is used with the Rényi divergence as a distance. Applied on two different populations composed of osteoporotic (OP) patients and control (CT) subjects, a classification rate of 98% is achieved which provides a good discrimination between OP patients and CT subjects.
Published: 2012

50. Kernel-Based Laplacian Smoothing Method for 3D Mesh Denoising

Author: Hicham Badri, Mohammed El Hassouni, Driss Aboutajdine, Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), LRIT, Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Université Mohammed V de Rabat [Agdal] (UM5), Université Mohammed V de Rabat [Agdal] (UM5), and Springer Verlag
Subjects: Mathematical optimization, Noise reduction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], symbols.namesake, Simple (abstract algebra), Gaussian noise, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Kernel (statistics), symbols, Polygon mesh, Laplacian smoothing, Linear combination, Algorithm, Laplace operator, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics
Abstract: International audience; In this paper, we present an improved Laplacian smoothing technique for 3D mesh denoising. This method filters directly the vertices by updating their positions. Laplacian smoothing process is simple to implement and fast, but it tends to produce shrinking and oversmoothing effects. To remedy this problem, firstly, we introduce a kernel function in the Laplacian expression. Then, we propose to use a linear combination of denoised instances. This combination aims to reduce the number of iterations of the desired method by coupling it with a technique that leadsto oversmoothing. Experiments are conducted on synthetic triangular meshes corrupted by Gaussian noise. Results show that we outperform some existing methods in terms of objective and visual quality.
Published: 2012
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