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Papers by madan lal

Research paper thumbnail of Face Recognition Using Pca, Lda and Various Distance Classifiers

Journal of Global Research in Computer Sciences, Apr 10, 2013

Face recognition has become a major field of interest these days. Face recognition algorithms are... more Face recognition has become a major field of interest these days. Face recognition algorithms are used in a wide range of applications such as security control, crime investigation, and entrance control in buildings, access control at automatic teller machines, passport verification, identifying the faces in a given databases. This paper discusses different steps involved in face recognition using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) and the different distance measures that can be used in face recognition.

Research paper thumbnail of Face Recognition Using Pca, Lda and Various Distance Classifiers

Journal of Global Research in Computer Science, Apr 10, 2013

Face recognition has become a major field of interest these days. Face recognition algorithms are... more Face recognition has become a major field of interest these days. Face recognition algorithms are used in a wide range of applications such as security control, crime investigation, and entrance control in buildings, access control at automatic teller machines, passport verification, identifying the faces in a given databases. This paper discusses different steps involved in face recognition using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) and the different distance measures that can be used in face recognition.

Research paper thumbnail of Study of Face Recognition Techniques: A Survey

International Journal of Advanced Computer Science and Applications, 2018

With the rapid growth in multimedia contents, among such content face recognition has got much at... more With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. In this survey paper, we have tried to address most endeavoring face features such as pose invariance, aging, illuminations and partial occlusion. They are considered to be indispensable factors in face recognition system when realized over facial images. This paper also studies state of the art face detection techniques, approaches, viz. Eigen face, Artificial Neural Networks (ANN), Support Vector Machines (SVM), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor Wavelets, Elastic Bunch Graph Matching, 3D morphable Model and Hidden Markov Models. In addition to the aforementioned works, we have mentioned different testing face databases which include AT & T (ORL), AR, FERET, LFW, YTF, and Yale, respectively for results analysis. However, aim of this research is to provide comprehensive literature review over face recognition along with its applications. And after in depth discussion, some of the major findings are given in conclusion.

Research paper thumbnail of Comparative Study of Different Image Enhancement Techniques

International journal of computer and technology, Jun 30, 2012

Research paper thumbnail of A Relook and Renovation over State-of-Art Salt and Pepper Noise Removal Techniques

International Journal of Image, Graphics and Signal Processing, 2016

Speckle is a multiplicative noise that degrades the quality of ultrasound images and its presence... more Speckle is a multiplicative noise that degrades the quality of ultrasound images and its presence makes the visual inspection difficult. In addition, it limits the professional application of image processing techniques such as automatic lesion segmentation. So speckle reduction is an essential step before further processing of ultrasonic images. Numerous techniques have been developed to preserve the edges while reducing speckle noise, but these filters avoid smoothing near the edges to preserve fine details. The objective of this work is to suggest a new technique that enhances B-Scan breast ultrasound images by increasing the speckle reduction capability of an edge sensitive filter. In the proposed technique a local statics based filter is applied in the non homogeneous regions, on the output of an edge preserving filter and an edge map is used to retain the original edges. Experiments are conducted using synthetic test image and real time ultrasound images. The effectiveness of the proposed technique is evaluated qualitatively by experts and quantitatively in terms of various quality metrics. Results indicate that proposed method can reduce more noise and simultaneously preserve important diagnostic edge information in breast ultrasound images.

Research paper thumbnail of Comparative Analysis of B-Mode Breast Ultrasound Image Enhancement Techniques

International Journal of Computer Applications, 2015

Acquisition of ultrasound images is cheap and noninvasive as it does not require ionizing radiati... more Acquisition of ultrasound images is cheap and noninvasive as it does not require ionizing radiations as compared to other medical imaging techniques but the problem with these images lies in its inherent characteristics like speckle noise and low contrast. In this paper the performance of various image enhancement techniques are compared by applying them on B-Mode breast ultrasound images (BUS) and by using the essential quantitative metrics like signal to noise ratio (SNR) , Edge Preserving Index (EPI) and Structured Similarity Index (SSIM).

Research paper thumbnail of A Comparitive Survey Of Various Segmentation Techniques

International Journal of Innovative Research and Development, May 31, 2013

Segmentation or the delineation of object boundaries in medical images remains a necessary step t... more Segmentation or the delineation of object boundaries in medical images remains a necessary step to obtain qualitative and quantitative measurements. Among these images, Ultrasound images plays a crucial role because the acquisition of these images is non invasive, cheap and does not require ionizing radiations compared to other medical imaging techniques. Due to acoustic interferences and artifacts, the automatic segmentation of anatomical structures in ultrasound imagery becomes a real challenge. Thus, to enhance the capabilities of ultrasound as a qualitative tool in clinical medicine, here we discuss the ultrasound image segmentation methods, focusing on techniques developed for medical. First, we discuss the formation of ultrasound images and conventional methods of image segmentation. After that we present the formulated methods for ultrasound image segmentation concerning the three largest areas of ultrasound imaging. Next section explains the validation degree that has been done in different application areas of ultrasound. In last section we conclude by referencing some papers which have introduced original ideas that exhibited particular usefulness in clinical domain specific to the ultrasound segmentation problem.

Research paper thumbnail of Automatic Seed Point Selection in B-Mode Breast Ultrasound Images

In order to reduce the processing time and complexity to detect the boundary of lesions in breast... more In order to reduce the processing time and complexity to detect the boundary of lesions in breast ultrasound (BUS) images, first step is selection of region of interest (ROI), which subsequently needs selection of seed point. Seed point is starting point that lies inside the lesion region. After selection of seed point, region growing techniques are used for segmentation of lesions or for selection of region of interest. Seed point can be selected manually, but it needs human interaction. To design a fully automatic breast ultrasound computer-aided diagnosis (CAD) system, an automatic seed point selection technique is required. In this paper, an automatic seed point detection technique is proposed. This technique is applied on 108 BUS images (57 benign and 51 malignant). Results are compared with other available methods. Quantitative experiment results show that this method could find the proper seed point for 95.3% BUS Images.

Research paper thumbnail of Face Recognition Using Pca, Lda and Various Distance Classifiers

Journal of Global Research in Computer Sciences, Apr 10, 2013

Face recognition has become a major field of interest these days. Face recognition algorithms are... more Face recognition has become a major field of interest these days. Face recognition algorithms are used in a wide range of applications such as security control, crime investigation, and entrance control in buildings, access control at automatic teller machines, passport verification, identifying the faces in a given databases. This paper discusses different steps involved in face recognition using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) and the different distance measures that can be used in face recognition.

Research paper thumbnail of Face Recognition Using Pca, Lda and Various Distance Classifiers

Journal of Global Research in Computer Science, Apr 10, 2013

Face recognition has become a major field of interest these days. Face recognition algorithms are... more Face recognition has become a major field of interest these days. Face recognition algorithms are used in a wide range of applications such as security control, crime investigation, and entrance control in buildings, access control at automatic teller machines, passport verification, identifying the faces in a given databases. This paper discusses different steps involved in face recognition using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) and the different distance measures that can be used in face recognition.

Research paper thumbnail of Study of Face Recognition Techniques: A Survey

International Journal of Advanced Computer Science and Applications, 2018

With the rapid growth in multimedia contents, among such content face recognition has got much at... more With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. In this survey paper, we have tried to address most endeavoring face features such as pose invariance, aging, illuminations and partial occlusion. They are considered to be indispensable factors in face recognition system when realized over facial images. This paper also studies state of the art face detection techniques, approaches, viz. Eigen face, Artificial Neural Networks (ANN), Support Vector Machines (SVM), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor Wavelets, Elastic Bunch Graph Matching, 3D morphable Model and Hidden Markov Models. In addition to the aforementioned works, we have mentioned different testing face databases which include AT & T (ORL), AR, FERET, LFW, YTF, and Yale, respectively for results analysis. However, aim of this research is to provide comprehensive literature review over face recognition along with its applications. And after in depth discussion, some of the major findings are given in conclusion.

Research paper thumbnail of Comparative Study of Different Image Enhancement Techniques

International journal of computer and technology, Jun 30, 2012

Research paper thumbnail of A Relook and Renovation over State-of-Art Salt and Pepper Noise Removal Techniques

International Journal of Image, Graphics and Signal Processing, 2016

Speckle is a multiplicative noise that degrades the quality of ultrasound images and its presence... more Speckle is a multiplicative noise that degrades the quality of ultrasound images and its presence makes the visual inspection difficult. In addition, it limits the professional application of image processing techniques such as automatic lesion segmentation. So speckle reduction is an essential step before further processing of ultrasonic images. Numerous techniques have been developed to preserve the edges while reducing speckle noise, but these filters avoid smoothing near the edges to preserve fine details. The objective of this work is to suggest a new technique that enhances B-Scan breast ultrasound images by increasing the speckle reduction capability of an edge sensitive filter. In the proposed technique a local statics based filter is applied in the non homogeneous regions, on the output of an edge preserving filter and an edge map is used to retain the original edges. Experiments are conducted using synthetic test image and real time ultrasound images. The effectiveness of the proposed technique is evaluated qualitatively by experts and quantitatively in terms of various quality metrics. Results indicate that proposed method can reduce more noise and simultaneously preserve important diagnostic edge information in breast ultrasound images.

Research paper thumbnail of Comparative Analysis of B-Mode Breast Ultrasound Image Enhancement Techniques

International Journal of Computer Applications, 2015

Acquisition of ultrasound images is cheap and noninvasive as it does not require ionizing radiati... more Acquisition of ultrasound images is cheap and noninvasive as it does not require ionizing radiations as compared to other medical imaging techniques but the problem with these images lies in its inherent characteristics like speckle noise and low contrast. In this paper the performance of various image enhancement techniques are compared by applying them on B-Mode breast ultrasound images (BUS) and by using the essential quantitative metrics like signal to noise ratio (SNR) , Edge Preserving Index (EPI) and Structured Similarity Index (SSIM).

Research paper thumbnail of A Comparitive Survey Of Various Segmentation Techniques

International Journal of Innovative Research and Development, May 31, 2013

Segmentation or the delineation of object boundaries in medical images remains a necessary step t... more Segmentation or the delineation of object boundaries in medical images remains a necessary step to obtain qualitative and quantitative measurements. Among these images, Ultrasound images plays a crucial role because the acquisition of these images is non invasive, cheap and does not require ionizing radiations compared to other medical imaging techniques. Due to acoustic interferences and artifacts, the automatic segmentation of anatomical structures in ultrasound imagery becomes a real challenge. Thus, to enhance the capabilities of ultrasound as a qualitative tool in clinical medicine, here we discuss the ultrasound image segmentation methods, focusing on techniques developed for medical. First, we discuss the formation of ultrasound images and conventional methods of image segmentation. After that we present the formulated methods for ultrasound image segmentation concerning the three largest areas of ultrasound imaging. Next section explains the validation degree that has been done in different application areas of ultrasound. In last section we conclude by referencing some papers which have introduced original ideas that exhibited particular usefulness in clinical domain specific to the ultrasound segmentation problem.

Research paper thumbnail of Automatic Seed Point Selection in B-Mode Breast Ultrasound Images

In order to reduce the processing time and complexity to detect the boundary of lesions in breast... more In order to reduce the processing time and complexity to detect the boundary of lesions in breast ultrasound (BUS) images, first step is selection of region of interest (ROI), which subsequently needs selection of seed point. Seed point is starting point that lies inside the lesion region. After selection of seed point, region growing techniques are used for segmentation of lesions or for selection of region of interest. Seed point can be selected manually, but it needs human interaction. To design a fully automatic breast ultrasound computer-aided diagnosis (CAD) system, an automatic seed point selection technique is required. In this paper, an automatic seed point detection technique is proposed. This technique is applied on 108 BUS images (57 benign and 51 malignant). Results are compared with other available methods. Quantitative experiment results show that this method could find the proper seed point for 95.3% BUS Images.