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The process of aligning one image, in the coordinate system of another is called registration. Image registration is vital in the medical domain and is used for diagnosis, therapy planning, and treatment of diseases. Due to its huge applicability and importance, medical image registration has emerged to be a separate domain of research. Beginning from the invasive landmark based registration, innumerable algorithms have been proposed to register two images of the human physiology. However, a breakthrough in the literature occurred when an information theory based measure, mutual information was used to register two images. Since then a large number of new algorithms have developed, which use mutual information for fully automatic registration of medical images. This paper is a survey of these algorithms. Beginning from its development, it discusses about some of the major works done on mutual information based image registration. Some comparative studies with other algorithms have also been discussed. The paper ends with a discussion of the developments in medical image registration algorithms post mutual information, which primarily include deep neural network (DNN) based algorithms. [ABSTRACT FROM AUTHOR]

The problem of pursuing the data items of a large database whose distances to a query item are the least is known as Similarity Search (Nearest Neighbor Search) problem. There exist various algorithms to address this problem. Some of the well known algorithms are i) exact algorithms ii) approximation algorithms and iii) randomized algorithms. This paper has made study only on exact and approximation algorithms because randomized algorithm produces approximate results with some probability. Recently, there are several approximation algorithms are proposed by the researchers because this type of algorithms minimizes the problem of Curse of Dimensionality. This paper mainly has two major sections. In first section, various methods under exact and approximation algorithms are discussed with regard to storage, preprocessing and query time. In the second section, efficient algorithms for similarity search suitable for certain physiological characteristics based biometric systems are considered. Biometric system has five main steps viz acquisition of Image, pre-processing, extraction of features, matching and making final decision. In this paper, indexing algorithms for similarity search suitable for iris trait based on different features are discussed in detail. Since the nature of features are distinct and different in biometric traits, there does not exist a universal (one unique) solution which can apply to all traits of biometric systems. Various performance measures like Penetration Rate and Hit Rate are used to determine the correct recognition rate with top best match (rank-1 accuracy). [ABSTRACT FROM AUTHOR]

The purpose of this paper is to give an overview of various well known medical image registration techniques with a special focus on registration between anatomical and functional medical images. Examples of anatomical medical images (AMI) are Computer Tomography (CT), Magnetic Resonance Images (MRI), X-ray radiographs and ultrasound etc. whereas Positron Emission Tomography (PET), Single Photon Emission Tomography (SPECT) and fMRI are examples of functional medical images (FMI). Irrespective of such types (AMI or FMI), every case can be considered as a medical imaging modality. All these modalities are widely used by clinicians to study the structure/functionality of human body parts for diagnosis and treatment. It is frequently required to combine PET/SPECT with CT/MRI to simultaneous study the metabolic and molecular information received through PET/SPECT with fine anatomical details observed by CT/MRI. This concurrent study will help in the diagnosis and localization of many diseases like cancer, blockage in coronary arteries and brain-related diseases like Parkinson, Alzheimer etc. Further, in many cases, clinicians are required to co-register one or more anatomical images with functional images, for example, ultrasound-guided biopsy fused with PET and MRI. This registration can be done either at the hardware level or at the software level. The introduction of integrated PET-CT machine increases the acceptability of hardware-based registration systems as compared to software-based methods among the medics. One possible reason for this is the lack of validation of results achieved through software-based registration methods. On the other hand, software-based registration methods also have many advantages over the hardware-based registration systems like lesser exposure to radiation and no need for new investment on hardware etc. In this paper, both the methods with their merits and demerits are discussed in detail. [ABSTRACT FROM AUTHOR]

Face stands out as a preferable biometric trait for automatic human authentication as it is intuitive and non-intrusive. This paper investigates various feature-based automatic face recognition approaches in detail. High degree of freedom in head movement and human emotion leads a face recognition system to face critical challenges in terms of pose, illumination and expression. Human face also undergoes irreversible changes due to aging. These factors makes the process of face recognition non trivial and hard. This paper also provides a review of the facial recognition approaches individually dealing with these issues. Applications of face recognition in the forensic domain sometimes needs identification using a scanned facial image. The scenario is quite useful to get investigative leads. Important approaches for the same are also been discussed in the manuscript. Recent developments in the low-cost image capturing devices has flooded the facial image databases with a lot of images, at the same time availability of GPU based compute power has helped develop deep learning approaches to handle the face recognition at a very accurate and massive level. The same has also been surveyed and analyzed in the manuscript. [ABSTRACT FROM AUTHOR]

Abstract Biometric authentication involves identification/verification of an individual based on his physiological or behavioral characteristics. Fingerprint, a physiological characteristic, is an impression developed on a surface touched by a human fingertip. As the use of fingerprint recognition grows, more and more people get registered to the system and therefore the size of biometric database increases. During identification when a new fingerprint is provided and the task is to find the most similar fingerprint from the database, it essentially involves searching the entire database. Identification becomes very compute intensive for large databases. If we can somehow reduce the search space from the entire database to a small size list, the identification would become cost-effective. One possibility is to use locality sensitive hashing based approaches. The key idea is to choose an appropriate representation of the fingerprint and to device an indexing approach around it. Such a technique would, instead of directly comparing the query fingerprint with all the fingerprints stored in the database, make a preprocessing to produce a small size candidate list of fingerprints and then search within the list. The candidate list contains the target fingerprint with certain probabilistic guarantees. Indexing is challenging for biometric databases due to various factors such as the presence of the variable number of features, absence of structural information like order, the presence of occlusion and illumination in the image etc. This paper presents a survey of indexing schemes used for fingerprint databases. These schemes have been classified into four broad categories, namely texture-based, minutiae-based, hybrid and deep learning based schemes. The schemes broadly cover the use of Level-1, Level-2, texture, and deep features. [ABSTRACT FROM AUTHOR]

In this paper, a multibiometric system that fuses slap fingerprints, palm dorsal vein, and hand geometry for accurate person authentication is proposed. The proposed system simultaneously acquires slap images and infrared (IR) hand dorsal image from which slap fingerprints, palm dorsal veins, and IR hand geometry are extracted. Simultaneous acquisition reduces the acquisition time and helps to improve user acceptability. The slap segmentation is accomplished using the knowledge of the approximate finger location and hand type (either left or right) obtained from the simultaneously acquired IR hand dorsal image. Multibiometric fusion based on serial methodology has been proposed for consolidating the matching scores of slap fingerprints, palm dorsal vein, and IR hand geometry. It ensures better performance in terms of accuracy and time. Experimental results indicate that authentication using slap fingerprints can be improved by incorporating the knowledge from IR hand images. Further, it depicts that the fusion of slap fingerprint, palm dorsal vein, and IR hand geometry can help to achieve the best performance. [ABSTRACT FROM AUTHOR]

Orientation field (OF) plays a crucial role in singular point detection, fingerprint image enhancement, fingerprint matching, fingerprint indexing, fingerprint synthesis, fingerprint registration and fingerprint classification. Thus, an accurate OF estimation algorithm is proposed in this paper. It presents a novel OF regularization algorithm based on variational approach, which aims to preserve the genuine OF in the areas containing uniform flow and to accurately reconstruct the OF in bad quality areas. Estimated OF may be spurious in singular points close-by areas thus, it is further refined by weighted OF modeling based on Fourier basis. Experimental results are conducted on a publicly available database, FVC2004DB1A in terms of singular point detection and deviation in OF. It demonstrated that the proposed algorithm exhibit better performance that the state of the art algorithms. [ABSTRACT FROM AUTHOR]

A slap fingerprint based verification system generally is highly secure. But it cannot handle the problems of temporal deformation and pose variation. In this paper, a template update algorithm has been proposed to ensure better performance of the system. During verification, each single fingerprint is matched and matching scores of all fingerprints are fused using an adaptive score level fusion. The performance of the proposed system has been evaluated on a challenging database containing 1800 slap-images acquired from 150 subjects. Experimental results show that the accuracy is increased by more than 3.5%. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient multi-modal authentication system which makes use of palm-dorsa vein pattern. There are four levels of fusion in the system and they are multi-algorithm fusion, data fusion, feature fusion and score fusion. Multi-algorithm fusion is applied to extract genuine vein patterns from a vein image by using various vein extraction algorithms. All false vein patterns are eliminated from the extracted patterns through data fusion. Three types of features are obtained from each extracted vein pattern and they are shape features, minutiae and features obtained from hand boundary shape. Third level of fusion is at feature level to fuse minutiae and shape features. Finally, fused features and hand boundary shape features are matched to obtain matching scores which are fused at score level. The proposed system has been tested on the database acquired from 4120 images of 1030 subjects. It has achieved an accuracy of 100%. Experimental results reveal that it performs better than other existing systems. [ABSTRACT FROM AUTHOR]

Slap fingerprint scanner can simultaneously acquire fingerprint of four fingers of a human hand in a single image. Subsequently, the image is required to be segmented to get fingerprints of individual fingers. The paper proposes a novel and efficient technique to extract individual fingerprints. It applies a divide and conquer strategy by using force field and heuristics. The technique has been tested on two slap image databases viz. IITK-4Slap-Rural and IITK-4Slap-Student and has achieved high segmentation accuracy. [ABSTRACT FROM AUTHOR]

This paper proposes an accurate and efficient multi-modal authentication system that makes use of palm and knuckleprint samples. Biometric images are transformed using the proposed sign of local gradient ( SLG ). Corner features are extracted from vcode and hcode and are tracked using geometrically and statistically constrained Lucas and Kanade tracking algorithm. The proposed highly uncorrelated features ( HUF ) measure is used to match two query images. The proposed system is tested on publicly available PolyU and CASIA palmprint databases along with PolyU Knuckleprint database. Several sets of chimeric bi-modal as well as multimodal databases are created in order to test the proposed system. Experimental results reveal that the proposed multi-modal system achieves CRR of 100% with an EER as low as 0.01% over all created chimeric multimodal datasets. [ABSTRACT FROM AUTHOR]

Tomographic image reconstruction has a wide variety of applications ranging from engineering applications to medical applications. Algebraic reconstruction methods, used to obtain the solutions of tomographic image reconstruction problems, are very slow in nature. This performance bottleneck has been discussed in detail in the present work. This paper encompasses a parallel (multi-processor based and multi-processor multi-GPU based) single-view coded multiplicative algebraic reconstruction technique. It has been found that parallel implementation of this algorithm helps in removing the performance bottleneck without compromising with quality of reconstruction. It has been also found that if one uses four processors to reconstruct an image of 512 × 512 × 512 volume size, then the multi-processor based algorithm takes 1997 s to perform one swap of 200 projections taken over a span of 360°. The use of four processors leads to an increase in speed of 2.39 in comparison with a single processor. Further, the proposed multi-processor multi-GPU based algorithm takes 186 s to perform the same reconstruction by using four GPUs, resulting in an increase in speed of 25.7 in comparison with a single processor. We are able to process 42 projections per minute by using the multi-processor multi-GPU based algorithm. The algorithm is applicable to online laminographic applications. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes an ear recognition technique which makes use of 3D along with co-registered 2D ear images. It presents a two-step matching technique to compare two 3D ears. In the first step, it computes salient 3D data points from 3D ear images with the help of local 2D feature points of co-registered 2D ear images. Subsequently, it uses these salient 3D points to coarsely align 3D ear images. In the second step, it performs final matching of coarsely aligned 3D ear images by using a Generalized Procrustes Analysis (GPA) and Iterative Closest Point (ICP) based matching technique (GPA-ICP). The proposed technique has been tested on 1780 images of 404 subjects (two or more images per subject) of University of Notre Dame public database-Collection J2 (UND-J2) which consists of co-registered 2D and 3D ear images with scale and pose variations. It has achieved a verification accuracy of 98.30% with an equal error rate of 1.8%. [Copyright &y& Elsevier]

Abstract: This paper makes use a morphing technique to increase embedding efficiency and embedding capacity of a cover image. It has modified F5 algorithm (Westfeld, 2001) [1] which provides higher security and embedding capacity in transform domain such that in the same cover image larger amount of data can be embedded. In this paper, the embedding capacity of the cover image has been improved by increasing the non-zero DCT coefficients. Experimental results show that for the test images under consideration, it can achieve the improvement of embedding capacity by about 53% and has better embedding efficiency in transform domain as compared to the original F5 algorithm for the same cover image. [Copyright &y& Elsevier]

Purpose: Almost 30% of malignancies in women of developing countries are gynecological and brachytherapy is an integral part of management of these patients. Reports of complications (both acute and late) of high-dose-rate (HDR) intracavitary brachytherapy are sparse in world literature due to relatively small number of gynecological malignancies, particularly in advanced stage, in developed countries. High-dose-rate brachytherapy is gaining popularity in developing countries due to scientific and economic reasons. Here we are reporting our experience regarding acute complications of intracavitary brachytherapy (events occurring within 30 days of insertion needing hospitalization or death) and their causes to improve the quality of management, so that the already low incidence of acute complications can be further reduced. Material and methods: From February 2004 to December 2012, a total of 1947 patients with uterine cancer were treated by HDR intracavitary brachytherapy in the Department of Radiotherapy, of a tertiary cancer centre of a developing country, 86% of them were cervical cancer and 14% endometrial cancer. Excluding the post-operative patients, a total of 4285 insertions were done in 1527 patients with intact uterus (eligible for analysis) and acute complications were analyzed. Results: Out of 4285 intracavitary brachytherapy insertions in gynecological malignancy patients, only 12 mortality and 239 morbidity instances needing hospitalization were documented and most of them were in cervical carcinoma patients. Conclusions: Our results have indicated that acute complications can be minimized by pre-treatment management of co-morbidities, decreasing the time of operative lithotomy position and bed rest, avoidance of 'conscious sedation' in selected cases etc. Routine post insertion CT scan if done in all patients in all insertions, then only, uterine perforations can be detected early and prompt management can reduce both the mortality and morbidity to a great extent. [ABSTRACT FROM AUTHOR]

Abstract: HIV/HCV co-infection provides a model to determine the role of immunity on HCV transmission and evolution. In this study HCV transmission and evolution were evaluated in 6 HCV seroconverters in HIV-infected subjects with a wide range of CD4 cell count. The HCV envelope E1/E2 sequences were analyzed for transmission bottleneck, viral diversity/divergence, immune pressure, and mutations of HLA class I/II restricted epitopes. HCV infection started with transmission bottleneck in all HIV-infected individuals. During the 1.0–2.0 years of infection there was a shift of viral quasispecies in majority of the subjects from one to next visit. However, HCV diversity, divergence, mutations in HLA class I/II restricted and virus neutralizing epitopes were similar in all subjects regardless of CD4 cell count at the time of HCV infection. Our results suggest that HCV transmission and evolution in HIV-infected subjects may not be influenced by host CD4 cell count at the time of infection. [Copyright &y& Elsevier]

Abstract: This paper presents a technique for automatic ear detection from 3D profile face range images. The proposed technique localizes ear by using inherent structural details of the ear in 3D range data and is invariant to rotation and scale. It makes use of connected components of a graph constructed using the edges of the depth map image of the range data. The main advantages of the proposed technique over other existing techniques are of two folds. First, the proposed technique does not require any registered 2D image for the detection of ear in 3D. Second, it is inherently rotation and scale invariant and can detect left and right ear simultaneously without imposing any additional computational cost. To demonstrate the effectiveness of the technique, experiments are conducted on University of Notre Dame public database, Collection J2 (UND-J2) which consists of 3D profile face range images with scale and pose variations. Experimental results are found to be encouraging and reveal the effectiveness of the proposed technique. Results are also compared with the existing 3D ear detection techniques. [Copyright &y& Elsevier]

Cervical tissue-based organ cultures have been used successfully to evaluate microbicides for toxicity and antiviral activity. The antimicrobial peptide retrocyclin RC-101 has been shown to have potent anti-HIV activity in cell culture.To evaluate RC-101 in organ culture for toxicity and its ability to block HIV-1 transmission across cervical mucosa.A cervical tissue-based organ culture was used to measure antiviral activity of RC-101. Cytotoxicity in tissues was determined by immunostaining of cellular proteins and by measuring inflammatory cytokines using real-time reverse transcriptase-polymerase chain reaction and Luminex technology.RC-101 blocked transmission of both R5 and X4 HIV-1 across cervical mucosa in this organ culture model. Furthermore, film-formulated RC-101 exhibited potent antiviral activity in organ culture. Such antiviral activity of RC-101 was retained in the presence of semen and vaginal fluid. RC-101 showed no cytotoxicity in cervical tissue. Furthermore, RC-101 did not induce proinflammatory cytokine response in tissues. RC-101 also did not have any effect on natural killer cell activity and proliferation of CD4 and CD8 cells and did not show chemotactic activity.Therefore, because of strong antiviral activity and low cytotoxicity in cervical tissues, RC-101 should be considered as an excellent microbicide candidate against HIV-1. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes an efficient technique for automatic localization of ear from side face images. The technique is rotation, scale and shape invariant and makes use of the connected components in a graph obtained from the edge map of the side face image. It has been evaluated on IIT Kanpur database consisting of 2672 side faces with variable sizes, rotations and shapes and University of Notre Dame database containing 2244 side faces with variable background and poor illumination. Experimental results reveal the efficiency and robustness of the technique. [Copyright &y& Elsevier]

This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. [ABSTRACT FROM AUTHOR]

Traditional nomenclatures of specifying cutting tool geometries are two-dimensional (2D) in nature. The present work presents a paradigm to model the geometries of a variety of twist drills in terms of three-dimensional (3D) parameters. The work outlines the construction of a detailed computer-aided design (CAD) model for a fluted twist drill and establishes a new 3D definition for the geometry of drill in terms of biparametric surface patches. The flutes of the drill are modeled as helicoidal surfaces. For this, sectional geometry of tip-to-tip profile is developed and then swept. The geometric model of the shank is developed separately. The transitional surfaces are modeled as bicubic Bèzier surfaces. With this methodology, we propose a new 3D nomenclature for drill geometries in terms of 3D rotational angles. The relations necessary to map the proposed three-dimensional angles to two-dimensional conventional angles, known as forward mapping and their reverse relations (inverse mapping) are also developed. The new paradigm offers immense technological advantages in terms of numerous downstream applications. [ABSTRACT FROM AUTHOR]

An efficient algorithm is presented to label the connected components in array representation of very huge 2-D images that one works with in remote sensing applications. A new data structure is suggested to maintain the equivalence table that makes use of a modified version of Union-Find algorithms. The operations supported by the equivalence table enable aggressive reuse of labels and bound the size of the table by ⌊N/2⌋+1, for a N×N image. It is also shown that the maintenance of the table has an overall linear amortized cost. [Copyright &y& Elsevier]

In this paper, we have studied the problem of finding the neighbors of a node in a quadtree. We have proposed a variation in the quadtree representation which has helped in finding the neighbors efficiently. We have presented algorithms for construction and maintenance of our quadtree. [ABSTRACT FROM AUTHOR]

Examines the relation of the shedding patterns of HIV type 1 (HIV-1) with the cell compartmentation of HIV-1 between blood and semen. Flow cytometry analysis of CD4[sup +] HIV gag-pol RNA-positive cells in seminal mononuclear cells; Correlation of seminal virus load with HIV transcription in seminal mononuclear cells; Phylogenetic tree of HIV-1 envelope sequence from HIV-1 RNA from semen and blood plasma.

Human face detection along with its localization is a difficult task when the face is presented in the cluttered scene in an unconstrained scenario that might be with arbitrary pose variations, occlusions, random backgrounds and infrared (IR) environment. This paper proposes a novel face detection method which can address some of these issues and challenges quite successfully during face detection in unconstrained as well as infrared environments. It makes use of Fast Successive Mean Quantization Transform (FastSMQT) features for image enhancement and feature representation to deal with illumination and sensor insensitiveness. A split up Sparse Network of Winnows (SNoW) with Winnow updating rule is then exploited to speed up the original SNoW classifier. Finally, the features and classifiers are combined together with skin detection algorithm for face detection in crowd image and head orientation correction of near infrared faces. The proposed face detector is robust in handling pose, occlusion, illumination, blur and low image resolution. The experiment is performed on six challenging and publicly available databases, viz. BIOID, LFW, FDDB, UFI, WIDER FACE and IIT Delhi near infrared. The experimental results depict that the proposed method outperforms traditional as well as some advanced methods in detecting unconstrained and infrared faces under challenging situations. [ABSTRACT FROM AUTHOR]

Adrenal neuroblastomas, although quite common in children, are extremely rare in adulthood. Here, we are reporting the case of a 47-year-old male who presented with right flank pain and had a palpable mass in the same region. Contrast-enhanced computed tomography showed an irregular, poorly marginated heterogeneous mass lesion arising from the right suprarenal position. Urinary catecholamines were within normal limits. There was no evidence of metastatic disease. The mass was resected en-block along with the right kidney. Histopathologic examination revealed the diagnosis of a neuroblastoma. Adjuvant chemotherapy was instituted, but the pain recurred after 9months. Despite subsequent chemotherapy, the mass continued to grow over the next 6months with further infiltration into the liver and surrounding muscles. The patient has currently been started on external palliative radiation. We have also reviewed the literature to present a discussion on presentation, diagnosis, and management of this rare tumor. [ABSTRACT FROM AUTHOR]

Colorectal carcinoma is very rare in childhood. In this case report, we depict a ten-year-old girl who presented with features of intestinal obstruction which turned out to be due to poorly differentiated mucin secreting adenocarcinoma of descending colon. Only increased awareness of this malignancy in this age-group and a high index of suspicion can help when a child complains of persistent pain of abdomen, altered bowel habits or rectal bleeding, and may provide diagnosis at an earlier stage, thereby improving the prognosis. [ABSTRACT FROM AUTHOR]

Discusses issues concerning in vitro models of mucosal HIV transmission. Study findings showing that non-human primates demonstrated that cervical epithelium is impermeable to the small tracer molecules lanthanum nitrate; Possible mechanisms for the viral transmission; Response to concerns over whether the transmission seen in an organ culture experiment was due to leakage around the tissue; Reiteration that the organ culture is effective in the study of HIV transmission in women.

Authenticating important documents by identifying individuals using handwritten signatures make signature verification a critical task. Interpersonal similarity and intrapersonal variation of individuals along with high skilled imitation of signature structure make automatic signature verification a challenging task. In such scenarios, a signature verification system should detect the small differences between genuine and forged signatures with high efficacy. This paper proposed a novel approach towards offline signature verification where a hybrid deep learning network, consisting of a Convolutional Neural Network and a Bidirectional Long Short Term Memory network is used. Signature written with freehand and an imitation of it are almost identical structurally. Deep Neural Network is used to recognize skilled forgery from genuine signatures because of its capability to learn critical details and subtle patterns from the image pixels. A Convolutional Neural Network is trained, and the trained network is then used to extract diverse features of the signature images. The generated feature vectors are then used for classification using Bidirectional Long Short Term Memory. The hybrid deep learning network classifies the input signature as skilled forgery or genuine with high accuracy. For this work, state-of-the-art datasets, such as, GPDS-300, GPDS-Bengali, GPDS-Devanagari, CEDAR, BHSig260-Bengali, BHSig260-Hindi, and a local dataset, Meitei Mayek signature are used. In order to verify the robustness of the system, different multi-scripted offline signatures belonging to multi-lingual Indian society, are used for evaluation. The experimental results determined from multi-scripted signatures, exhibit that the proposed system is found comparable to many state-of-the-art systems and in some specific cases, it out performs some of the existing systems. • Hybrid system (CNN-BiLSTM) increases the performance of signature verification. • Writer independent approach enables verification of new signature without registering. • Validated using multi-scripted signatures, so increases the system's robustness. [ABSTRACT FROM AUTHOR]

In this paper, hand dorsal images acquired under infrared light are used to design an accurate personal authentication system. Each of the image is segmented into palm dorsal and fingers which are subsequently used to extract palm dorsal veins and infrared hand geometry features respectively. A new quality estimation algorithm is proposed to estimate the quality of palm dorsal which assigns low values to the pixels containing hair or skin texture. Palm dorsal is enhanced using filtering. For vein extraction, information provided by the enhanced image and the vein quality is consolidated using a variational approach. The proposed vein extraction can handle the issues of hair, skin texture and variable width veins so as to extract the genuine veins accurately. Several post processing techniques are introduced in this paper for accurate feature extraction of infrared hand geometry features. Matching scores are obtained by matching palm dorsal veins and infrared hand geometry features. These are eventually fused for authentication. For performance evaluation, a database of 1500 hand images acquired from 300 different hands is created. Experimental results demonstrate the superiority of the proposed system over existing systems. [ABSTRACT FROM AUTHOR]

This paper proposes a finger-knuckle-print based authentication system by fusing multiple texture features. It contains new algorithms for extracting region of interest (ROI) with the help of curvature Gabor filters, image quality parameters, ROI enhancement using gradient based ordinal relationships, and dissimilarity measure for matching. The proposed system has been tested on the largest publicly available finger-knuckle-print PolyU database consisting of 7920 finger-knuckle-print images obtained from 165 subjects in two sessions. It has shown good performance. [ABSTRACT FROM AUTHOR]

Fractional calculus is an abstract idea exploring interpretations of differentiation having non-integer order. For a very long time, it was considered as a topic of mere theoretical interest. However, the introduction of several useful definitions of fractional derivatives has extended its domain to applications. Supported by computational power and algorithmic representations, fractional calculus has emerged as a multifarious domain. It has been found that the fractional derivatives are capable of incorporating memory into the system and thus suitable to improve the performance of locality-aware tasks such as image processing and computer vision in general. This article presents an extensive survey of fractional-order derivative-based techniques that are used in computer vision. It briefly introduces the basics and presents applications of the fractional calculus in six different domains viz. edge detection, optical flow, image segmentation, image de-noising, image recognition, and object detection. The fractional derivatives ensure noise resilience and can preserve both high and low-frequency components of an image. The relative similarity of neighboring pixels can get affected by an error, noise, or non–homogeneous illumination in an image. In that case, the fractional differentiation can model special similarities and help compensate for the issue suitably. The fractional derivatives can be evaluated for discontinuous functions, which help estimate discontinuous optical flow. The order of the differentiation also provides an additional degree of freedom in the optimization process. This study shows the successful implementations of fractional calculus in computer vision and contributes to bringing out challenges and future scopes. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes an efficient indexing technique for fingerprint database using minutiae based geometric hashing. This technique consists of two stages, known as indexing and searching. For an accurate match at the time of searching, it has proposed a fixed length feature vector built from each minutia, known as Minutia Binary Pattern. Unlike any existing geometric based indexing technique, the proposed technique inserts each minutia along with the feature vector exactly once into a hash table. As a result, it reduces both computational and memory costs. Since minutiae of all fingerprint images in the database are found to be well distributed into the hash table, no rehashing is required. Experiments over FVC 2004 datasets prove the superiority of the proposed indexing technique against well known geometric based indexing techniques. [Copyright &y& Elsevier]

Background: The CD8 Antiviral Factor (CAF) suppresses viral transcription from the HIV-1 Long Terminal Repeat (LTR) promoter in a non-cytolytic manner. However, the region on the LTR upon which CAF acts is unknown. Our objective was to determine the region on the LTR upon which CAF acts to suppress HIV-1 transcription. Methods: Serial deletions of the LTR from the 5' end and inactivating point mutations were made. Results: Serial deletions of the LTR from the 5' end indicated the importance of a short ~120 bp segment, containing the 3 SpI sites, CATA box (used by HIV-1 instead of the TATA box) and TAR region, in the suppressive process. Introduction of deletions or inactivating point mutations in the SpI sites or deletion of the TAR region did not abolish CAF-mediated transcriptional suppression. Yet, CAF-mediated transcriptional suppression was still retained in the HIV-1 CATA-TAR segment. Conclusion: CAF is able to suppress transcription from the LTR lacking all the elements upstream of the CATA box. Our results suggest that the HIV-1 CATA box may be responsible for CAF-mediated suppression of transcription from the HIV-1 LTR. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a novel approach that models the process of aging using Active Appearance Models (AAMs) and Ensemble of Classifiers for Age Estimation. The approach treats the problem of age estimation as a combination of classification and regression problems. In this approach, face image is encoded using the statistically driven AAMs which uses both shape and appearance models to form a combined model to represent the face image as a feature vector. A global classifier is then used to obtain a rough idea about the age by distinguishing between child/teen-hood and adulthood, while final age estimation is made using regression functions. To reduce misclassification error, an ensemble containing various classifiers trained on multiple dissimilarities has been used. The images thus classified are passed on to different aging functions for further accurate age estimation. Experiments have been performed on the publicly available FG-NET database and the Center for Vital Longevity Face Database to test the approach. It has been observed that the proposed approach has the lowest Mean Absolute Error (MAE) and the highest Cumulative Score when compared with other published results. It is further tested on IIT Kanpur database consisting of images of age group 18–34 acquired under semi-controlled environment. [Copyright &y& Elsevier]

Abstract: This paper presents an efficient face recognition system which is invariant to partial occlusion. The proposed system makes use of Eigen faces and Gabor wavelet filters to handle occlusion. It divides each face image into a set of sub-images and makes use of Gabor filters to extract features from non-occluded sub-images. Matching between two face images is performed by comparing features of non-occluded regions of two images. The system has been tested on AR face database containing 2600 occluded images of 100 subjects. Experimental results reveal better performance compared to all well known systems which are invariant to partial occlusion. [Copyright &y& Elsevier]

Abstract: Financial inclusion is the delivery of financial services at affordable cost to sections of disadvantaged and low income segments of society. It has several leakages such as security threats and transaction frauds in the available system. The use of biometrics in the financial inclusion is a near perfect solution to such security threats. Such a biometric system should be fast enough to recognise/identify a subject from a large database. This paper proposes an indexing technique for a biometric database consisting of variable number of features with high dimensions. The technique makes use of geometric properties of principal components of features. Unlike existing indexing techniques, it inserts fewer features into a hash table. It reduces both computational and memory costs significantly. The geometric properties of principal components of features are found to be robust to handle translation and rotation effects. The proposed technique has been tested on palmprint biometric databases viz. PolyU [25], CASIA [26] and IITK which have 7752, 5239 and 549 images respectively. It is found to be more efficient than any other existing indexing techniques. [Copyright &y& Elsevier]

Abstract: This paper proposes an efficient method to synthesize pose of an image. Pose synthesis is used to predict the face image with minimal error at a desired pose from a given pose. It is frequently required in many applications like production of animated movies, in forensic science and generation of 3D face geometry, etc. It uses principal component analysis (PCA) in conjunction with linear object classes (LOC) method (). The face image of a pose is modelled as shape and texture vectors and the LOC method is applied on these two vectors of training set separately. The principal components of shape vector give a smaller number of significant dimensions along which the best linear approximation using LOC for the shape vector is calculated. Even though the given vector is approximated using only these dimensions, the error in approximation is significantly less compared to approximating pose image using all dimensions of shape vector. The proposed method is tested on CMU PIE face database and it is found to be significant improvement over the well known linear object classes method. [Copyright &y& Elsevier]

Abstract: This paper explores the effectiveness of a novel multibiometric system that is resulted from the fusion of the electrocardiogram (ECG) with an unobtrusive biometric face and another biometric fingerprint which is known to be a least obtrusive for efficient individual authentication. The unimodal systems of the face and the fingerprint biometrics are neither secure nor they can achieve the optimum performance. Using the ECG signal as one of the biometrics offer advantage to a multibiometric system that ECG is inherited to an individual which is confidential, secured and difficult to be forged. It has an inherent feature of vitality signs that ensures a strong protection against spoof attacks to the system. Transformation based score fusion technique is used to measure the performance of the fused system. In particular, the weighted sum of score rule is used where weights are computed using equal error rate (EER) and match score distributions of the unimodal systems. The performance of the proposed multibiometric system is measured using EER and receiver operating characteristic (ROC) curve. The results show the optimum performance of the multibiometric system fusing the ECG signal with the face and fingerprint biometrics which is achieved to an EER of 0.22%, as compared to the unimodal systems that have the EER of 10.80%, 4.52% and 2.12%, respectively for the ECG signal, face and fingerprint biometrics. [Copyright &y& Elsevier]

Abstract: This paper proposes a hierarchical approach to retrieve an iris image efficiently from for a large iris database. This approach is a combination of both iris color and texture. Iris color is used for indexing and texture is used for retrieval of iris images from the indexed iris database. An index which is determined from the iris color is used to filter out the images that are not similar to the query image in color. Further, iris texture features of those filtered images, are used to determine the images which are similar to the query image. The iris color information helps to design an efficient indexing scheme based on color indices. The color indices are computed by averaging the intensity values of all red and blue color pixels. Kd-tree is used for real-time indexing based on color indices. The iris texture features are obtained through Speeded Up Robust Features (SURF) algorithm. These features are used to get the query’s corresponding image at the top best match. The performance of the proposed indexing scheme is compared with two well known iris indexing schemes () on UPOL () and UBIRIS () iris databases. It is observed that combination of iris color and texture improves the performance of iris recognition system. [Copyright &y& Elsevier]

Abstract: We previously reported that selected mutations of highly conserved arginine residues within the LLP regions of HIV-1ME46 gp41 had diverse effects on Env function. In the current study, we sought to test if the observed LLP mutant phenotypes would be similar in HIV-189.6. The results of the current studies revealed that the LLP-1 mutations conferred reduced Env incorporation, infectivity, and replication phenotypes in both viruses, while homologous LLP-2 mutations had differential phenotypical effects between the two strains. In particular, several of the 89.6 LLP-2 mutant viruses were replication defective in CEMX174 cells despite having increased levels of Env incorporation, and with both strains, there were differential effects on infectivity. This comparison of homologous point mutations in two different strains of HIV supports the role of LLPs as determinants of Env function, but reveals for the first time the influence of virus strain on LLP mutant phenotypes. [Copyright &y& Elsevier]

Retrocyclins are cyclic antimicrobial peptides that exhibit potent activity towards a broad range of primary and laboratory-adapted strains of human immunodeficiency virus type 1 (HIV-1) in vitro. The current study shows that RC-101, an analogue of retrocyclin, prevented HIV-1 infection in an organ-like construct of human cervicovaginal tissue and retained full activity in the presence of vaginal fluid. The peptide remained within the cervicovaginal tissues throughout the 9-day incubation period without altering tissue viability, inducing damage or inducing the release of inflammatory cytokines. Collectively, these data support the potential development of RC-101 as a topical microbicide to prevent HIV-1 infection and transmission. [ABSTRACT FROM AUTHOR]

The persistence of human immunodeficiency virus type 1 (HIV-1) infection in the presence of robust host immunity has been associated in part with variation in viral envelope proteins leading to antigenic variation and escape from neutralizing antibodies. Previous studies of natural neutralization escape mutants have predominantly focused on gp120 and gp41 ectodomain sequence variations that alter antibody binding via changes in conformation or glycosylation pattern of the Env, likely due to the immune pressure exerted on the exposed ectodomain component of the glycoprotein. Here, we show for the first time a novel mechanism by which point mutations in the intracytoplasmic tail of the transmembrane component (gp41) of envelope can render the virus resistant to neutralization by monoclonal antibodies and broadly neutralizing polyclonal serum antibodies. Point mutations in a highly conserved structural motif within the intracytoplasmic tail resulted in decreased binding of neutralizing antibodies to the Env ectodomain, evidently due to allosteric changes both in the gp41 ectodomain and in gp120. While receptor binding and infectivity of the mutant virus remained unaltered, the changes in Env antigenicity were associated with an increase in neutralization resistance of the mutant virus. These studies demonstrate the structurally integrated nature of gp120 and gp41 and underscore a previously unrecognized potentially critical role for even minor sequence variation of the intracytoplasmic tail in modulating the antigenicity of the ectodomain of HIV-1 envelope glycoprotein complex. [ABSTRACT FROM AUTHOR]

Two highly conserved cationic amphipathic α-helical motifs, designated lentivirus lytic peptides 1 and 2 (LLP-1 and LLP-2), have been characterized in the carboxyl terminus of the transmembrane (TM) envelope glycoprotein (Env) of lentiviruses. Although various properties have been attributed to these domains, their structural and functional significance is not clearly understood. To determine the specific contributions of the Env LLP domains to Env expression, processing, and incorporation and to viral replication and syncytium induction, site-directed LLP mutants of a primary dualtropic infectious human immunodeficiency virus type 1 (HIV-1) isolate (ME46) were examined. Substitutions were made for highly conserved arginine residues in either the LLP-1 or LLP-2 domain (MX1 or MX2, respectively) or in both domains (MX4). The HIV-1 mutants with altered LLP domains demonstrated distinct phenotypes. The LLP-1 mutants (MX1 and MX4) were replication defective and showed an average of 85% decrease in infectivity, which was associated with an evident decrease in gp41 incorporation into virions without a significant decrease in Env expression or processing in transfected 293T cells. In contrast, MX2 virus was replication competent and incorporated a full complement of Env into its virions, indicating a differential role for the LLP-1 domain in Env incorporation. Interestingly, the replication-competent MX2 virus was impaired in its ability to induce syncytia in T-cell lines. This defect in cell-cell fusion did not correlate with apparent defects in the levels of cell surface Env expression, oligomerization, or conformation. The lack of syncytium formation, however, correlated with a decrease of about 90% in MX2 Env fusogenicity compared to that of wild-type Env in quantitative luciferase-based cell-cell fusion assays. The LLP-1 mutant MX1 and MX4 Envs also exhibited an average of 80% decrease in fusogenicity. Altogether, these results demonstrate for the first... [ABSTRACT FROM AUTHOR]

Background: The effect of antiretroviral therapy on seminal HIV shedding in the community remains unknown.Objective: To evaluate the effect of antiretroviral therapy on HIV shedding in semen.Design: Prospective cohort study.Setting: University hospital in Rio de Janeiro, Brazil.Patients: 93 HIV-infected men.Intervention: Antiretroviral therapy as prescribed by each patient's physician.Measurement: HIV RNA in semen and blood plasma before and after introduction of therapy.Results: At baseline, HIV RNA was detected in 69 semen samples (74%) and 89 blood samples (96%). Six months after introduction of therapy, HIV RNA was detected in 29 semen samples (33%) and 33 blood samples (38%). The mean reduction in levels of HIV RNA in semen at 6 months was 1.65 log10 units.Conclusions: Antiretroviral therapy reduces shedding of HIV in semen, which probably in tum reduces HIV transmissibility. However, a substantial proportion of patients may still be infectious and may have drug-resistant strains of the virus. [ABSTRACT FROM AUTHOR]

This paper presents an ensemble face recognition system which makes use of the novel local descriptor called Dense Local Graph Structure (D-LGS) which is exploited from symmetric LGS that and it uses additional graph structure in addition to its own local graph structure. This additional local graph structure is generated by finding additional corner pixel points through bilinear interpolation of neighborhood pixels. These corner pixels lead to most stable features and information related to local deformation of the image. In this proposed ensemble system, three classifiers, namely K-nearest neighbor, Chi-square and correlation coefficient are used. Further the proposed approach fuses the decisions obtained from individual classifiers through OR rule, majority voting and AND rule. To evaluate the performance of proposed ensemble system, the experiment is conducted with three face databases viz. AT&T (formerly The ORL Database of Faces), UFI and LFW face database. The ensemble face recognition system on the use of novel dense local graph structure has reached the accuracy of 100% on AT&T, 99.3488% on UFI and 87.3372% on LFW face database. Further, the templates of D-LGS are optimized using Genetic algorithm (GA) as part of 'curse-of-dimensionality' and the reduced number of templates give accuracies of 100% on AT&T and 99.2165% on LFW face database. [ABSTRACT FROM AUTHOR]