12 results on '"V. Amala Rani"'
Search Results
2. Efficient Hybrid Multimodal Image Fusion for Brain Images
- Author
-
V. Amala Rani and Dr.S. Lalithakumari
- Subjects
Discrete wavelet transform ,Fusion ,Image fusion ,General Computer Science ,business.industry ,Computer science ,Multimodal image ,General Engineering ,Computer vision ,Artificial intelligence ,business - Published
- 2020
- Full Text
- View/download PDF
3. ML Based Smart Energy Meter Observing & Bill Supervision Using Raspberry Pi
- Author
-
N. Praveen, D. Marshiana, T. Thaj Mary Delsy, P. Kartheek, and V. Amala Rani
- Subjects
Raspberry pi ,Power consumption ,business.industry ,Electricity meter ,Computer science ,Electrical engineering ,business ,Internet of Things - Published
- 2021
- Full Text
- View/download PDF
4. A Hybrid Fusion Model for Brain Tumor Images of MRI and CT
- Author
-
V. Amala Rani and S. Lalithakumari
- Subjects
Discrete wavelet transform ,021110 strategic, defence & security studies ,Fusion ,Hybrid image ,Image fusion ,Computer science ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,0211 other engineering and technologies ,Pattern recognition ,02 engineering and technology ,Hilbert–Huang transform ,Physics::Plasma Physics ,Computer Science::Computer Vision and Pattern Recognition ,Distortion ,Medical imaging ,Artificial intelligence ,Tomography ,business - Abstract
Multimodal medical image fusion helps to acquire more information about both the functional and structural informations. More over storage problems can also be addressed properly when the fusion process is adopted. A hybrid image fusion is being sought for an optimum algorithm for a better quality image. This proposed work describes about the multimodal image fusion framework based on empirical mode decomposition of images and fusion by discrete wavelet transform method. The obtained fused image by the proposed method consists of all the functional information and also the spatial characteristics of original image. No distortion is also present in the fused image. In this proposed work Magnetic Resonance Imaging (MRI), and Computerized Tomography (CT) images of brain are used for fusion. The fusion results obtained by this method are observed and quantitatively analyzed. The hybrid fusion response of this approach depicts the dominance of the acquired results.
- Published
- 2020
- Full Text
- View/download PDF
5. Medical Image Segmentation And Classification On Efficiently Fused Image Using Fast Fuzzy C Means Algorithm And Convolutional Neural Network
- Author
-
et. al., V. Amala Rani and et. al., V. Amala Rani
- Abstract
In the recent past, medical image processing plays significant role in diagnosis of disease using Computer Aided Diagnosis (CAD). In this research, we propose a novel approach for classification of medical images using Fast Fuzzy C-Means (FFCM) clustering and Convolutional Neural Networks (CNN). Initially, the images were pre-processed using filtering and enhancement techniques. Image filtering was performed using 2D Gabor Filter. This step helped to remove noise in the medical data. Then, image enhancement was performed using Edge Preservation-Contrast Limited Adaptive Histogram Equalization (EP-CLAHE) technique. Fusion of medical data belonging to different modality results in the generation of a single image that has extended information content and helps to increase the reliability of disease diagnosis. The images were fused using 2-Dimensional Double Density Wavelet Transform (2D-DDWT) and Empirical Principle Component Analysis (EPCA). Segmentation plays a crucial role in detecting tumor cells in medical images. Here, segmentation was performed using FFCM clustering algorithm. The FFCM clustering helps in achieving accurate segmentation results with reduced computational complexity. The efficiency and reliability of a classification algorithm depend on the type of features extracted from the classification data. In our research, Gray Level Co-Occurrence Matrix (GLCM) features were extracted from the segmented data. Deep Learning (DP) technique is widely used for classification of image using significant features with high accuracy and efficiency. Using these features, classification was performed using CNN. The images were classified into benign and malignant. The simulation was performed using publicly available datasets. The outcome of the research shows that the proposed scheme was very effective in the classification of tumor images. The classification performance of the proposed framework was validated using metrics like recall, precision, specificity, F-s
- Published
- 2021
6. Regulation of Speed for Driver Assistanceand Removal of Haze using Imageprocessing Algorithm
- Author
-
D. Jamuna Rani, T. Thaj Mary Delsy, V. Amala Rani, G Rajalakshmi, N R Krishnamoorthy, and Ebin.G. Thoomas
- Subjects
History ,Haze ,business.industry ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Process (computing) ,Single frame ,Video image ,Computer Science Applications ,Education ,Image (mathematics) ,Transmission (telecommunications) ,Computer vision ,Artificial intelligence ,Visibility ,business ,Boundary constraints - Abstract
The clarity of the outdoor scene images very bad due to the environmental condition result in hazy image. The process of removing the fog from that image is called dehazing. The dehazing process is very difficult in the moving image or video image. The proposed method should improve this problem for the smooth driving of the vehicles by controlling the speed by comparing the image and the scene of video taken during driving. The proposed method should remove the haze so that it will increase the visibility of the image and multi scene. The proposed method can improve the colour changes in the image which is caused by airlight. The single frame is used for the enhancement of the foggy image remove the fog using the transmission map which contains multilevel. We make use of boundary constraints and global airlight estimation is taken into account. The method is fast and noise-free that generally arise in such enhancement techniques.
- Published
- 2021
- Full Text
- View/download PDF
7. Implementation of hybrid model Converter for Photovoltaic Applications
- Author
-
D. Jamunarani, D. Marshiana, G. Rajalakshmi, V. Amala Rani, and S Bestley Joe
- Subjects
History ,Computer science ,Photovoltaic system ,Electronic engineering ,Hybrid model ,Computer Science Applications ,Education - Abstract
The increase in the use of non-conventional energy sources in our day to day life is to save our earth. The hybrid wind and photovoltaic power generation system allow supplying the load either individually or at the same time. This technique includes the Cuk and Sepic converters together and this eliminates the accessibility for extra input filters having high-frequency harmonics. The rapid changes in the atmospheric conditions can be control by using the Maximum Power Point Tracking technique because of its high tracking accuracy. To increase the output power and efficiency the Buck Boost and Sepic converters are used. Converters output ripple voltage can be reduced by the photovoltaic array voltage which can vary from 0 to 600V. The thin-film PV panels and the MPPT methodology is produced with the help of converters by reducing the stress occurred in voltage due to inverters and to work at 230V DC-bus voltage reducing Simulation is carried out MATLAB Simulink.
- Published
- 2021
- Full Text
- View/download PDF
8. HIV-1 induced differential expression of cell surface proteins in SupT1 cell lines
- Author
-
ian R, Anne Frank Joe, S Bestly Joe, Lalitha Kumari S, and V Amala Rani
- Subjects
Pulmonary and Respiratory Medicine ,Discrete wavelet transform ,Computer science ,020208 electrical & electronic engineering ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Data_CODINGANDINFORMATIONTHEORY ,02 engineering and technology ,Peak signal-to-noise ratio ,Set partitioning in hierarchical trees ,Computer Science::Computer Vision and Pattern Recognition ,Compression (functional analysis) ,Pediatrics, Perinatology and Child Health ,Color depth ,Compression ratio ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Algorithm ,Encoder ,Image compression - Abstract
The storage facility of image and image transfer is an extensive appliance in image compression. Image compression techniques require the proper and effective transforms and encoding methods to reach the aim. In this work, discrete wavelet transform based image compression algorithm is used for decomposing the image. The effectiveness of different Encoder loops are analyzed based on the values of peak signal to noise ratio (PSNR), compression ratio (CR), means square error (MSE) and bits per pixel (BPP). The optimum encoding loop for compression is also found based on the results.
- Published
- 2018
- Full Text
- View/download PDF
9. CAN PROTOCOL DRIVERLESS TRAIN CONTROL SYSTEM
- Author
-
V. Amala Rani .
- Subjects
Engineering ,business.industry ,Mobile phone ,Node (networking) ,Control system ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Train ,business ,Computer security ,computer.software_genre ,Protocol (object-oriented programming) ,computer ,CAN bus - Abstract
This paper addresses the train running autonomously without any human operators. Provides information to avoid train to train collisions, over speeding problem, signaling errors and unmanned railway crossing incidents. This afford a way for a passenger to know the train location, speed and direction in real time from anywhere in India through his mobile phone.CAN protocol interconnect all the train compartments with embedded network to ensure safety and security of passengers during disasters occurring within trains such as bomb blasts and fire outbreaks. This make obtainable way for a passenger to know the train location, speed and direction in real time from anywhere in India through his mobile phone. The CAN node is used to ensure the safety and comfort of the passengers. It also have audio speakers to inform the passengers about the approaching station and also to provide alert messages during a crisis situation.
- Published
- 2014
- Full Text
- View/download PDF
10. Recent Medical Image Fusion Techniques: A Review
- Author
-
V. Amala Rani and S. Lalithakumari
- Subjects
021110 strategic, defence & security studies ,Image fusion ,medicine.diagnostic_test ,business.industry ,020208 electrical & electronic engineering ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,0211 other engineering and technologies ,Public Health, Environmental and Occupational Health ,Process (computing) ,Robotics ,02 engineering and technology ,Single-photon emission computed tomography ,Contourlet ,Positron emission tomography ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Medical imaging ,Computer vision ,Artificial intelligence ,Complex wavelet transform ,business ,Mathematics - Abstract
Image fusion technique has been widely in use in many applications such as computer vision, surveillance, robotics, medical imaging, remote sensing etc. Medical image fusion plays a vital role to deal with medical issues reflected through images of human body, organs and cells. It is necessary to preserve the fused image in order to keep the relevant information of input images. It is also necessary to keep the fusion process away from introducing any artifacts or inconsistencies. More over image fusion techniques must provide a good quality and must enhance the applications of recent data. This paper elucidates the survey of recent literatures, which dealt medical images like magnetic resonance imaging (MRI), Computed Tomography (CT), Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) of brain. This paper reviews some of the recent medical image fusion algorithm such as Non Sampled Contourlet transform, Directive Contrast, Daubechies complex wavelet transform, Shift-invariant Shearlet transform etc. The merits and demerits of the various image fusion algorithm which developed by the authors is described in the paper. The survey emerges out the optimum fusion algorithm.
- Published
- 2019
- Full Text
- View/download PDF
11. Face and Finger Vein Recognition for Security Based Electronic Voting Machine Using Raspberry Pi
- Author
-
G Rajalakshmi, V. Amala Rani, D. Jamuna Rani, T. Thaj Mary Delsy, Praveen K. Pradeep, and S. Sidharthan
- Subjects
Scanner ,Electronic voting ,business.industry ,media_common.quotation_subject ,Public Health, Environmental and Occupational Health ,Image processing ,Finger vein recognition ,Raspberry pi ,Face (geometry) ,Voting ,Computer vision ,Artificial intelligence ,Face detection ,business ,media_common ,Mathematics - Abstract
The assist device for blind people is much needed in recent days. The gadgets in recent trends are digitized that the blind people are not capable of handling digitized applications hence in our project we design text to voice converter, that converts the eBooks, audiobooks to voice format. In this project the audiobook eBooks are fed into SD card reader after that the sd card reader is interfaced and the Arduino UNO converts the text file to Audio output. The audio books can be heard in headphone\speaker using Arduino UNO. This project is low cost it will be more useful for blind people. Secure voting must be necessary to avoid the fake voting. The problem of fake voting can be solved by using Face detection and Finger vein based Electronics Voting Machine (EVM) system. In electronic voting system the details of the voters are stored; the voting date is recorded and processed digitally. Most of the existing Electronic voting machines has been developed using Radio Frequency ID. In developing countries RFID for each person is not possible due to high cost efficiency. Image processing based EVM also introduced, but it not provides accurate results for the twin persons. The EVM with finger print also not providing the accurate results. So the modified EVM with face and finger vein was introduced to obtain the satisfied result. The Raspberry Pi plays major roll in this project. It is act as a on board CPU work on the operating system called rasbian OS. The necessary hardwires like, camera, finger vein scanner, EVM are connected with Rasperry Pi. The datas of all the voters along with the images of the face and the finger vein are already stored in the system. The camera capture the picture of the person then compare with the stored data and find whether the person is authorized person or not. Once the person is authorized then the next section scan the finger and compare with the data and inform to the system that whether known or unknown. If both face and finger vein are recognized then the voter can register their vote. The fake voting can be completely avoid using this voting method.
- Published
- 2019
- Full Text
- View/download PDF
12. CAN PROTOCOL DRIVERLESS TRAIN CONTROL SYSTEM
- Author
-
., V. Amala Rani, primary
- Published
- 2014
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.