Sanjay Talbar - Academia.edu (original) (raw)
Papers by Sanjay Talbar
2015 International Conference on Pervasive Computing (ICPC), 2015
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014
ABSTRACT Multimodality Medical image fusion is the process of extracting complementary informatio... more ABSTRACT Multimodality Medical image fusion is the process of extracting complementary information from various modality medical images and combing it for better visualization, accurate diagnosis and appropriate treatment planning. The combined single image is merging of anatomical and physiological variations. It allows accurate localization of cancer tissues and more helpful for estimation of target volume for radiation. The multimodal fusion algorithms presented in this paper utilizes Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Dual Tree Complex Wavelet Transform (DT-CWT), and Daubechies Complex Wavelet Transform (DCWT) to extract features of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images which are then combined based on various fusion rules. The performance and effectiveness of the algorithms are evaluated using Standard Deviation (σfus), Entropy (En), Fusion Factor (FusFac), Cross correlation (Rcorr) and Cross Entropy (CEn). The fused images of DCWT are superior over other frequency domain algorithms as per subjective and objective analysis.
2014 International Conference on Medical Imaging M Health and Emerging Communication Systems, Nov 1, 2014
International Journal of Modeling and Optimization, 2012
International Journal of Computer Applications, 2012
ABSTRACT The Object recognition is the task of finding and labeling parts of a two-dimensional (2... more ABSTRACT The Object recognition is the task of finding and labeling parts of a two-dimensional (2D) image of a scene that correspond to objects in the scene. In this paper, we have proposed an efficient approach using level set method for extracting object shape contour and convex hull as a shape invariant features to the Feed forward Neural Network classifier for object recognition. We extracted the shape contour by level set method. Then, we have obtained invariant shape feature, convex hull of the objects. This convex hull set serves as a pattern for the Neural Network. Initially Feed forward neural network trained on the odd data set and tested on even data set. Our approach is evaluated on the Amsterdam Library of Object Images collection, a large collection of object images containing 1000 objects recorded under various imaging circumstances. The experimental results clearly demonstrate that our approach significantly outperforms. The proposed method is shown to be effective under a wide variety of imaging conditions.
TENCON '91. Region 10 International Conference on EC3-Energy, Computer, Communication and Control Systems, 1991
2011 3rd International Conference on Electronics Computer Technology, 2011
In this paper, a simple, yet effective system for authenticated robot control applications is pre... more In this paper, a simple, yet effective system for authenticated robot control applications is presented. The system is based on face and hand gesture recognition. First, the user is verified using real dual-tree discrete wavelet transform (R-DT-DWT) based face recognition. The authenticated user is further allowed to have control over the required robot application using hand gesture recognition. Later, the
IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), 2007
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014
ABSTRACT Multimodality Medical image fusion is the process of extracting complementary informatio... more ABSTRACT Multimodality Medical image fusion is the process of extracting complementary information from various modality medical images and combing it for better visualization, accurate diagnosis and appropriate treatment planning. The combined single image is merging of anatomical and physiological variations. It allows accurate localization of cancer tissues and more helpful for estimation of target volume for radiation. The multimodal fusion algorithms presented in this paper utilizes Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Dual Tree Complex Wavelet Transform (DT-CWT), and Daubechies Complex Wavelet Transform (DCWT) to extract features of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images which are then combined based on various fusion rules. The performance and effectiveness of the algorithms are evaluated using Standard Deviation (σfus), Entropy (En), Fusion Factor (FusFac), Cross correlation (Rcorr) and Cross Entropy (CEn). The fused images of DCWT are superior over other frequency domain algorithms as per subjective and objective analysis.
ABSTRACT Data communication is transmission data from a point to another. Nowadays main issue in ... more ABSTRACT Data communication is transmission data from a point to another. Nowadays main issue in data communication is the security. It can provide a fine solution by encryption. The encryption algorithm is the mathematical process for performing encryption on data. The proposed algorithm supports for user desired security level and processing level. The algorithm provides security levels and their corresponding processing levels by generating random keys for the encryption/decryption process. This facility is achieved by using fuzzy logic. The results of the proposed encryption algorithm will be analyzed by comparing with other existing encryption algorithms. The aim of the research is to build a new algorithm using fuzzy sets requirement which will be more advanced than the existing encryption algorithms.
National Conference on Signal and Image Processing Applications, 2009
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014
SpringerBriefs in Applied Sciences and Technology, 2014
In this paper we address the problem of face recognition using edge information as independent co... more In this paper we address the problem of face recognition using edge information as independent components. The edge information is obtained by using Laplacian of Gaussian (LoG) and Canny edge detection methods then preprocessing is done by using Principle Component analysis (PCA) before applying the Independent Component Analysis (ICA) algorithm for training of images. The independent components obtained by ICA algorithm are used as feature vectors for classification. The Euclidean distance and Mahalanobis distance classifiers are used for testing of images. The algorithm is tested on two different databases of face images for variation in illumination and facial poses up to 1800rotation angle.
SpringerBriefs in Applied Sciences and Technology, 2013
SpringerBriefs in Applied Sciences and Technology, 2013
2015 International Conference on Pervasive Computing (ICPC), 2015
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014
ABSTRACT Multimodality Medical image fusion is the process of extracting complementary informatio... more ABSTRACT Multimodality Medical image fusion is the process of extracting complementary information from various modality medical images and combing it for better visualization, accurate diagnosis and appropriate treatment planning. The combined single image is merging of anatomical and physiological variations. It allows accurate localization of cancer tissues and more helpful for estimation of target volume for radiation. The multimodal fusion algorithms presented in this paper utilizes Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Dual Tree Complex Wavelet Transform (DT-CWT), and Daubechies Complex Wavelet Transform (DCWT) to extract features of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images which are then combined based on various fusion rules. The performance and effectiveness of the algorithms are evaluated using Standard Deviation (σfus), Entropy (En), Fusion Factor (FusFac), Cross correlation (Rcorr) and Cross Entropy (CEn). The fused images of DCWT are superior over other frequency domain algorithms as per subjective and objective analysis.
2014 International Conference on Medical Imaging M Health and Emerging Communication Systems, Nov 1, 2014
International Journal of Modeling and Optimization, 2012
International Journal of Computer Applications, 2012
ABSTRACT The Object recognition is the task of finding and labeling parts of a two-dimensional (2... more ABSTRACT The Object recognition is the task of finding and labeling parts of a two-dimensional (2D) image of a scene that correspond to objects in the scene. In this paper, we have proposed an efficient approach using level set method for extracting object shape contour and convex hull as a shape invariant features to the Feed forward Neural Network classifier for object recognition. We extracted the shape contour by level set method. Then, we have obtained invariant shape feature, convex hull of the objects. This convex hull set serves as a pattern for the Neural Network. Initially Feed forward neural network trained on the odd data set and tested on even data set. Our approach is evaluated on the Amsterdam Library of Object Images collection, a large collection of object images containing 1000 objects recorded under various imaging circumstances. The experimental results clearly demonstrate that our approach significantly outperforms. The proposed method is shown to be effective under a wide variety of imaging conditions.
TENCON '91. Region 10 International Conference on EC3-Energy, Computer, Communication and Control Systems, 1991
2011 3rd International Conference on Electronics Computer Technology, 2011
In this paper, a simple, yet effective system for authenticated robot control applications is pre... more In this paper, a simple, yet effective system for authenticated robot control applications is presented. The system is based on face and hand gesture recognition. First, the user is verified using real dual-tree discrete wavelet transform (R-DT-DWT) based face recognition. The authenticated user is further allowed to have control over the required robot application using hand gesture recognition. Later, the
IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), 2007
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014
ABSTRACT Multimodality Medical image fusion is the process of extracting complementary informatio... more ABSTRACT Multimodality Medical image fusion is the process of extracting complementary information from various modality medical images and combing it for better visualization, accurate diagnosis and appropriate treatment planning. The combined single image is merging of anatomical and physiological variations. It allows accurate localization of cancer tissues and more helpful for estimation of target volume for radiation. The multimodal fusion algorithms presented in this paper utilizes Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Dual Tree Complex Wavelet Transform (DT-CWT), and Daubechies Complex Wavelet Transform (DCWT) to extract features of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images which are then combined based on various fusion rules. The performance and effectiveness of the algorithms are evaluated using Standard Deviation (σfus), Entropy (En), Fusion Factor (FusFac), Cross correlation (Rcorr) and Cross Entropy (CEn). The fused images of DCWT are superior over other frequency domain algorithms as per subjective and objective analysis.
ABSTRACT Data communication is transmission data from a point to another. Nowadays main issue in ... more ABSTRACT Data communication is transmission data from a point to another. Nowadays main issue in data communication is the security. It can provide a fine solution by encryption. The encryption algorithm is the mathematical process for performing encryption on data. The proposed algorithm supports for user desired security level and processing level. The algorithm provides security levels and their corresponding processing levels by generating random keys for the encryption/decryption process. This facility is achieved by using fuzzy logic. The results of the proposed encryption algorithm will be analyzed by comparing with other existing encryption algorithms. The aim of the research is to build a new algorithm using fuzzy sets requirement which will be more advanced than the existing encryption algorithms.
National Conference on Signal and Image Processing Applications, 2009
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014
SpringerBriefs in Applied Sciences and Technology, 2014
In this paper we address the problem of face recognition using edge information as independent co... more In this paper we address the problem of face recognition using edge information as independent components. The edge information is obtained by using Laplacian of Gaussian (LoG) and Canny edge detection methods then preprocessing is done by using Principle Component analysis (PCA) before applying the Independent Component Analysis (ICA) algorithm for training of images. The independent components obtained by ICA algorithm are used as feature vectors for classification. The Euclidean distance and Mahalanobis distance classifiers are used for testing of images. The algorithm is tested on two different databases of face images for variation in illumination and facial poses up to 1800rotation angle.
SpringerBriefs in Applied Sciences and Technology, 2013
SpringerBriefs in Applied Sciences and Technology, 2013