I am interested in conducting research in areas related with image processing, machine learning, computer vision, artificial intelligence and medical image processing.
Digital Media is the main source of communication now a days. A drastic change emerged with the a... more Digital Media is the main source of communication now a days. A drastic change emerged with the access of internet to everyone, which made it possible to copy and distribute the digital content illegally. Digital Watermarking/Steganography has been used for digital media protection. Many techniques have been developed for effective watermarking. However, there is always a tradeoff between robustness and imperceptibility features of watermarking offered by these techniques. In this paper, we have proposed a method based on Full Counter Propagation Neural Network (FCPN) to train multiple grey or color cover images to produce a desired watermark image. We have used grey, binary and color images as watermarks. The results have proved the higher imperceptibility and robustness of this scheme when compared with the other available watermarking techniques.
International journal of innovative computing, information & control: IJICIC
Abstract. Requirement Prioritization is a very critical but often neglected area of re-quirement ... more Abstract. Requirement Prioritization is a very critical but often neglected area of re-quirement engineering. Experience has shown that without proper prioritization of re-quirements presented by various stakeholders, the end product usually fails to meet its objectives optimally. In ...
Paper presents directional weighted median base fuzzy filter for randomvalued impulse noise remov... more Paper presents directional weighted median base fuzzy filter for randomvalued impulse noise removal. In order to detect noise efficiently a fuzzy noise detection process is used whereas noise removal is performed by the directional weighted median based fuzzy filtering process. Proposed technique is compared with existing techniques based on peak-signal-to-noise-ratio (PSNR) and structural similarity index measure (SSIM). Simulations show that the noise removal capability of the proposed technique is much better than the existing techniques.
Image processing techniques have witnessed increased usage in various real world applications. Fo... more Image processing techniques have witnessed increased usage in various real world applications. For any image processing technique, such as image segmentation, restoration, edge detection, stereo matching etc., to be applied successfully, the image under consideration must contain all of the scene objects in focus. Usually, due to inadequate depth of field of optical lenses, especially with larger focal length, it becomes impossible to obtain an image in which all of the objects are in focus. Image fusion deals with creating an image by combining portions from other images to obtain an image in which all of the objects are in focus. In this paper, a novel feature-level multi-focus image fusion technique has been proposed which fuses multi-focus images using classification. Ten pairs of multi-focus images are first divided into blocks. The optimal block size for every image is found adaptively. The block feature vectors are fed to feed forward neural network. The trained neural network is then used to fuse any pair of multi-focus images. The results of extensive experimentation performed are presented to highlight the efficiency and usefulness of the proposed technique.
Engineering Applications of Artificial Intelligence
ABSTRACT Composite filters based on mathematical morphological operators (MMO) are getting consid... more ABSTRACT Composite filters based on mathematical morphological operators (MMO) are getting considerable attraction in image denoising. Most of such approaches depend on pre-fixed combination of MMO. In this paper, we proposed a genetic programming (GP) based approach for denoising magnetic resonance images (MRI) that evolves an optimal composite morphological supervised filter (FOCMSF) by combining the gray-scale MMO. The proposed method is divided into three modules: preprocessing module, GP module, and evaluation module. In preprocessing module, the required components for the development of the proposed GP based filter are prepared. In GP module, FOCMSF is evolved through evaluating the fitness of several individuals over certain number of generations. Finally, the evaluation module provides the mechanism for testing and evaluating the performance of the evolved filter. The proposed method does not need any prior information about the noise variance. The improved performance of the developed filter is investigated using the standard MRI datasets and its performance is compared with previously proposed methods. Comparative analysis demonstrates the superiority of the proposed GP based scheme over the existing approaches.
In matter of great importance, it is the innate behaviour for human beings to seek more than one ... more In matter of great importance, it is the innate behaviour for human beings to seek more than one consultant before making a decision. In such cases we weigh the individual opinions of experts on the basis of their competence and then combine them through some thought process in order to finalize the decision. In this paper we have proposed an idea of Particle Swarm Optimization (PSO) in order to optimize these weights which then better evaluate the competence of an expert. Weighted Majority Voting (WMV) is the most popular technique used to combine such opinions in an ensemble based classification. The weights associated to each base classifier in WMV on the basis of its competence are optimized under the influence of the basic idea of PSO. PSO has shown the stable performance on the selected datasets from UCI Repository and generally improved the performance of an ensemble system.
Brain tumor diagnosis is a very crucial task. This system provides an efficient and fast way for ... more Brain tumor diagnosis is a very crucial task. This system provides an efficient and fast way for diagnosis of the brain tumor. Proposed system consists of multiple phases. First phase consists of texture feature extraction from brain MR images. Second phase classify brain images on the bases of these texture feature using ensemble base classifier. After classification tumor region is extracted from those images which are classified as malignant using two-stage segmentation process. Segmentation consists of skull removal and tumor extraction phases. Quantitative results show that our proposed system performed very efficiently and accurately. We achieved accuracy of classification beyond 99%. Segmentation results also show that brain tumor region is extracted quite accurately.
With the improvements of technologies, software systems have been more complex then ever before. ... more With the improvements of technologies, software systems have been more complex then ever before. This requires new approaches to improve software development processes so that they sufficiently and efficiently meet these challenges. Requirement engineering in this regard facing many problems in which conflicts resolution gained very little popularity. In this paper we present motivation toward requirement conflicts resolution and discuss how resolution techniques from other domains can be applied in this area. We also proposed a new approach for conflicts resolution based on the idea of genetic algorithm. This model is applied to a case study to demonstrate how systematically resolution process can be optimized.
The study presents an efficient gender classification technique. The gender of a facial image is ... more The study presents an efficient gender classification technique. The gender of a facial image is the most prominent feature, and improvement in the existing gender classification methods will result in the high performance of the face retrieval and classification methods for large repositories. In this paper a new efficient gender classification method is proposed. First, the face part of the image is segmented using Viola and Jones face detection technique which excludes unwanted area from the image, so reducing image size. Histogram equalization is performed to normalize the illumination effect. Discrete Cosine Transform (DCT) is employed for feature extraction and sorting the features with high variance. K-nearest neighbor classifier (KNN) is used for classification. The face images used in this study were obtained from the Stanford university medical student (SUMS) frontal facial images database. The experimental results on the SUMS face database indicate that the proposed appro...
This paper presents a non-intrusive fatigue detection system based on the video analysis of drive... more This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The system relies on multiple visual cues to characterize the level of alertness of the driver. The parameters used for detecting fatigue are: eye closure duration measured through eye state information and yawning analyzed through mouth state information. Initially, the face is located through Viola-Jones face detection method to ensure the presence of driver in video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. Simultaneously, the pupils are also detected in the upper part of the face window on the basis of radii, inter-pupil distance and angle. The monitored information of eyes and mouth are further passed to Fuzzy Expert System (FES) that classifies the true state of the driver. The system has been tested using real data, with different sequences recorded in day and night driving condit...
ABSTRACT We propose a modified particle swarm optimization (MPSO) based method for Pseudo De-conv... more ABSTRACT We propose a modified particle swarm optimization (MPSO) based method for Pseudo De-convolution of the ill-posed inverse problem namely, the space-variant image degradation (SVD). In this paper, SVD is simulated by the pseudo convolution of different sub-regions of the image with different known blurring kernels and additive random noise with unknown variance. Two heuristic modifications are proposed in PSO: 1) Initialization of the swarm and 2) Mutation of the global best. Fuzzy logic is applied for the computation of regularization parameter (RP) to cater for the sensitivity of the problem. The computation of RP is crucial due to the additive noise in the SVD image. Thus mathematical morphology (MM) is applied for better extraction of spatial activity from the distorted image. The performance of the proposed method is evaluated with different test images and noise powers. Comparative analysis demonstrates the superiority of proposed restoration, in terms of quantitative measures, over well-known existing and state-of-the-art SVD approaches.
The authors in this study proposed facial expression recognition system in order to improve the e... more The authors in this study proposed facial expression recognition system in order to improve the expression recognition performance over the recently proposed systems. Feature sets for all training samples are constructed based on speed up robust feature descriptors. An ensemble of feature sets is then created incrementally. To achieve high diversity of ensemble, the dissimilarities between the training samples for each class are computed. This high diversity led to a high recognition rate. Experimentation on two publicly available datasets is performed. The system achieved 98?6% accuracy on JAFFE dataset and 96?3% accuracy on Multimedia Understanding Group dataset. The results of proposed system are compared with recently proposed work in this area and proved the soundness of the proposed method.
ABSTRACT The grouping of pixels based on some similarity criteria is called image segmentation. I... more ABSTRACT The grouping of pixels based on some similarity criteria is called image segmentation. In this paper the problem of color image segmentation is considered as a clustering problem and a fixed length genetic algorithm (GA) is used to handle it. The effectiveness of GA depends on the objective function (fitness function) and the initialization of the population. A new objective function is proposed to evaluate the quality of the segmentation and the fitness of a chromosome. In fixed length genetic algorithm the chromosomes have same length, which is normally set by the user. Here, a self organizing map (SOM) is used to determine the number of segments in order to set the length of a chromosome automatically. An opposition based strategy is adopted for the initialization of the population in order to diversify the search process. In some cases the proposed method makes the small regions of an image as separate segments, which leads to noisy segmentation. A simple ad hoc mechanism is devised to refine the noisy segmentation. The qualitative and quantitative results show that the proposed method performs better than the state-of-the-art methods.
ABSTRACT In this paper, a color difference based fuzzy filter is presented for fix and random-val... more ABSTRACT In this paper, a color difference based fuzzy filter is presented for fix and random-valued impulse noise. Noise detection scheme of two stages was applied to detect noise efficiently whereas for noise removal an improved Histogram based Fuzzy Color Filter (HFC) is presented. Pixels detected as noisy by the noise detection scheme are deliberated as candidate for the removal of noise. Candidate noisy pixels are then processed using a modified Histogram based Fuzzy Color Filter to estimate their non-noisy values. The idea of using multiple fuzzy membership functions is presented, so that best suitable membership function for local image statistics can be used automatically. In the proposed technique we have used three different types of fuzzy membership functions (bell-shaped, trapezoidal-shaped, and triangular-shaped) and their fuzzy number construction algorithms are proposed. Experimentation is also performed with three, five, and seven membership functions. Type and number of suitable fuzzy membership functions are then identified to remove noise. Comparison with the existing filtering techniques is established on the basis of objective quantitative measures including structural similarity index measure (SSIM) and peak-signal-to-noise-ratio (PSNR). Simulations show that this filter is superior to that of the existing state-of-the-art filtering techniques in removing fix and random-valued impulse noise whereas retaining the details of the image contents.
Authentication and copyright protection of information contents has always been a concern in prin... more Authentication and copyright protection of information contents has always been a concern in print media. The problem has become more critical with the increasing use of the Internet and digital technologies. Besides image, audio and video, the text is most extensively used medium travelling over the Internet. Digital libraries offer a quick and easy access to information such as e-books, archives, images, etc. However, making the protection of copyright is more complex and difficult. Increasing use of digital libraries, blogs and electronic commerce has made it necessary to protect digital contents. Digital watermarking came up as a solution for copyright protection problem. In this paper, we propose a novel text watermarking algorithm, which embeds the watermark image in the text (to be protected) logically using embedding algorithm and extract it later using the extraction algorithm. Experimental results demonstrate the effectiveness of the algorithm proposed in localized and dispersed attacks on the text. Objective evaluation methods like Normalized Hamming Distances (NHD), Peak-Signal-to-Noise-Ratio (PSNR), Weighted Peak-Signal-to-Noise-Ratio (WPSNR), Mean Structural Similarity Index Measures (MSSIM) and Normalized Absolute Error (NAE) metrics are used to measure the quality and similarity between original and extracted watermark images.
ABSTRACT Brain tumor is one of the major causes of death among other types of the cancers. Proper... more ABSTRACT Brain tumor is one of the major causes of death among other types of the cancers. Proper and timely diagnosis can prevent the life of a person to some extent. Therefore we have proposed an automated reliable system for the diagnosis of the brain tumor. Proposed system is a multi-stage system for brain tumor diagnosis and tumor region extraction. First, noise removal is performed as the preprocessing step on the brain MR images. Texture features are extracted from these noise free brain MR images. Next phase of the proposed system is classification that is based on these extracted features. Ensemble based SVM classification is used. More than 99% accuracy is achieved by the classification phase. After classification, proposed system extracts tumor region from tumorous images using multi-step segmentation. First step is skull removal and brain region extraction. Next step is separating tumor region from normal brain cells using FCM clustering. Results of the proposed technique show that tumor region is extracted quite accurately. This technique has been tested against the datasets of different patients received from Holy Family hospital and Abrar MRI & CT Scan center Rawalpindi.
Communications in Computer and Information Science, 2011
Global software development (GSD) outsourcing is a modern business strategy for producing high qu... more Global software development (GSD) outsourcing is a modern business strategy for producing high quality software at low cost. Most of the problems in Global software development (GSD) occur due to the lack of communication between stakeholders, time zone issues, cultural differences, etc. In this paper, our main emphasis will be to improve the Value-based requirement elicitation (VBRE) steps in GSD environment and also to overcome the major GSD environment problems while taking the process of requirement elicitation from valued stakeholders. Though this model works for every kind of project but, specifically it is good for generic software.
Proceedings of the 4th International Conference on Ubiquitous Information Technologies & Applications, 2009
Abstract: With rapid developments in the field of software products and services, it has assumed ... more Abstract: With rapid developments in the field of software products and services, it has assumed vital significance to define Value in a new perspective. With advent of new software engineering approaches like value based software engineering, this has become really relevant to ...
Digital Media is the main source of communication now a days. A drastic change emerged with the a... more Digital Media is the main source of communication now a days. A drastic change emerged with the access of internet to everyone, which made it possible to copy and distribute the digital content illegally. Digital Watermarking/Steganography has been used for digital media protection. Many techniques have been developed for effective watermarking. However, there is always a tradeoff between robustness and imperceptibility features of watermarking offered by these techniques. In this paper, we have proposed a method based on Full Counter Propagation Neural Network (FCPN) to train multiple grey or color cover images to produce a desired watermark image. We have used grey, binary and color images as watermarks. The results have proved the higher imperceptibility and robustness of this scheme when compared with the other available watermarking techniques.
International journal of innovative computing, information & control: IJICIC
Abstract. Requirement Prioritization is a very critical but often neglected area of re-quirement ... more Abstract. Requirement Prioritization is a very critical but often neglected area of re-quirement engineering. Experience has shown that without proper prioritization of re-quirements presented by various stakeholders, the end product usually fails to meet its objectives optimally. In ...
Paper presents directional weighted median base fuzzy filter for randomvalued impulse noise remov... more Paper presents directional weighted median base fuzzy filter for randomvalued impulse noise removal. In order to detect noise efficiently a fuzzy noise detection process is used whereas noise removal is performed by the directional weighted median based fuzzy filtering process. Proposed technique is compared with existing techniques based on peak-signal-to-noise-ratio (PSNR) and structural similarity index measure (SSIM). Simulations show that the noise removal capability of the proposed technique is much better than the existing techniques.
Image processing techniques have witnessed increased usage in various real world applications. Fo... more Image processing techniques have witnessed increased usage in various real world applications. For any image processing technique, such as image segmentation, restoration, edge detection, stereo matching etc., to be applied successfully, the image under consideration must contain all of the scene objects in focus. Usually, due to inadequate depth of field of optical lenses, especially with larger focal length, it becomes impossible to obtain an image in which all of the objects are in focus. Image fusion deals with creating an image by combining portions from other images to obtain an image in which all of the objects are in focus. In this paper, a novel feature-level multi-focus image fusion technique has been proposed which fuses multi-focus images using classification. Ten pairs of multi-focus images are first divided into blocks. The optimal block size for every image is found adaptively. The block feature vectors are fed to feed forward neural network. The trained neural network is then used to fuse any pair of multi-focus images. The results of extensive experimentation performed are presented to highlight the efficiency and usefulness of the proposed technique.
Engineering Applications of Artificial Intelligence
ABSTRACT Composite filters based on mathematical morphological operators (MMO) are getting consid... more ABSTRACT Composite filters based on mathematical morphological operators (MMO) are getting considerable attraction in image denoising. Most of such approaches depend on pre-fixed combination of MMO. In this paper, we proposed a genetic programming (GP) based approach for denoising magnetic resonance images (MRI) that evolves an optimal composite morphological supervised filter (FOCMSF) by combining the gray-scale MMO. The proposed method is divided into three modules: preprocessing module, GP module, and evaluation module. In preprocessing module, the required components for the development of the proposed GP based filter are prepared. In GP module, FOCMSF is evolved through evaluating the fitness of several individuals over certain number of generations. Finally, the evaluation module provides the mechanism for testing and evaluating the performance of the evolved filter. The proposed method does not need any prior information about the noise variance. The improved performance of the developed filter is investigated using the standard MRI datasets and its performance is compared with previously proposed methods. Comparative analysis demonstrates the superiority of the proposed GP based scheme over the existing approaches.
In matter of great importance, it is the innate behaviour for human beings to seek more than one ... more In matter of great importance, it is the innate behaviour for human beings to seek more than one consultant before making a decision. In such cases we weigh the individual opinions of experts on the basis of their competence and then combine them through some thought process in order to finalize the decision. In this paper we have proposed an idea of Particle Swarm Optimization (PSO) in order to optimize these weights which then better evaluate the competence of an expert. Weighted Majority Voting (WMV) is the most popular technique used to combine such opinions in an ensemble based classification. The weights associated to each base classifier in WMV on the basis of its competence are optimized under the influence of the basic idea of PSO. PSO has shown the stable performance on the selected datasets from UCI Repository and generally improved the performance of an ensemble system.
Brain tumor diagnosis is a very crucial task. This system provides an efficient and fast way for ... more Brain tumor diagnosis is a very crucial task. This system provides an efficient and fast way for diagnosis of the brain tumor. Proposed system consists of multiple phases. First phase consists of texture feature extraction from brain MR images. Second phase classify brain images on the bases of these texture feature using ensemble base classifier. After classification tumor region is extracted from those images which are classified as malignant using two-stage segmentation process. Segmentation consists of skull removal and tumor extraction phases. Quantitative results show that our proposed system performed very efficiently and accurately. We achieved accuracy of classification beyond 99%. Segmentation results also show that brain tumor region is extracted quite accurately.
With the improvements of technologies, software systems have been more complex then ever before. ... more With the improvements of technologies, software systems have been more complex then ever before. This requires new approaches to improve software development processes so that they sufficiently and efficiently meet these challenges. Requirement engineering in this regard facing many problems in which conflicts resolution gained very little popularity. In this paper we present motivation toward requirement conflicts resolution and discuss how resolution techniques from other domains can be applied in this area. We also proposed a new approach for conflicts resolution based on the idea of genetic algorithm. This model is applied to a case study to demonstrate how systematically resolution process can be optimized.
The study presents an efficient gender classification technique. The gender of a facial image is ... more The study presents an efficient gender classification technique. The gender of a facial image is the most prominent feature, and improvement in the existing gender classification methods will result in the high performance of the face retrieval and classification methods for large repositories. In this paper a new efficient gender classification method is proposed. First, the face part of the image is segmented using Viola and Jones face detection technique which excludes unwanted area from the image, so reducing image size. Histogram equalization is performed to normalize the illumination effect. Discrete Cosine Transform (DCT) is employed for feature extraction and sorting the features with high variance. K-nearest neighbor classifier (KNN) is used for classification. The face images used in this study were obtained from the Stanford university medical student (SUMS) frontal facial images database. The experimental results on the SUMS face database indicate that the proposed appro...
This paper presents a non-intrusive fatigue detection system based on the video analysis of drive... more This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The system relies on multiple visual cues to characterize the level of alertness of the driver. The parameters used for detecting fatigue are: eye closure duration measured through eye state information and yawning analyzed through mouth state information. Initially, the face is located through Viola-Jones face detection method to ensure the presence of driver in video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. Simultaneously, the pupils are also detected in the upper part of the face window on the basis of radii, inter-pupil distance and angle. The monitored information of eyes and mouth are further passed to Fuzzy Expert System (FES) that classifies the true state of the driver. The system has been tested using real data, with different sequences recorded in day and night driving condit...
ABSTRACT We propose a modified particle swarm optimization (MPSO) based method for Pseudo De-conv... more ABSTRACT We propose a modified particle swarm optimization (MPSO) based method for Pseudo De-convolution of the ill-posed inverse problem namely, the space-variant image degradation (SVD). In this paper, SVD is simulated by the pseudo convolution of different sub-regions of the image with different known blurring kernels and additive random noise with unknown variance. Two heuristic modifications are proposed in PSO: 1) Initialization of the swarm and 2) Mutation of the global best. Fuzzy logic is applied for the computation of regularization parameter (RP) to cater for the sensitivity of the problem. The computation of RP is crucial due to the additive noise in the SVD image. Thus mathematical morphology (MM) is applied for better extraction of spatial activity from the distorted image. The performance of the proposed method is evaluated with different test images and noise powers. Comparative analysis demonstrates the superiority of proposed restoration, in terms of quantitative measures, over well-known existing and state-of-the-art SVD approaches.
The authors in this study proposed facial expression recognition system in order to improve the e... more The authors in this study proposed facial expression recognition system in order to improve the expression recognition performance over the recently proposed systems. Feature sets for all training samples are constructed based on speed up robust feature descriptors. An ensemble of feature sets is then created incrementally. To achieve high diversity of ensemble, the dissimilarities between the training samples for each class are computed. This high diversity led to a high recognition rate. Experimentation on two publicly available datasets is performed. The system achieved 98?6% accuracy on JAFFE dataset and 96?3% accuracy on Multimedia Understanding Group dataset. The results of proposed system are compared with recently proposed work in this area and proved the soundness of the proposed method.
ABSTRACT The grouping of pixels based on some similarity criteria is called image segmentation. I... more ABSTRACT The grouping of pixels based on some similarity criteria is called image segmentation. In this paper the problem of color image segmentation is considered as a clustering problem and a fixed length genetic algorithm (GA) is used to handle it. The effectiveness of GA depends on the objective function (fitness function) and the initialization of the population. A new objective function is proposed to evaluate the quality of the segmentation and the fitness of a chromosome. In fixed length genetic algorithm the chromosomes have same length, which is normally set by the user. Here, a self organizing map (SOM) is used to determine the number of segments in order to set the length of a chromosome automatically. An opposition based strategy is adopted for the initialization of the population in order to diversify the search process. In some cases the proposed method makes the small regions of an image as separate segments, which leads to noisy segmentation. A simple ad hoc mechanism is devised to refine the noisy segmentation. The qualitative and quantitative results show that the proposed method performs better than the state-of-the-art methods.
ABSTRACT In this paper, a color difference based fuzzy filter is presented for fix and random-val... more ABSTRACT In this paper, a color difference based fuzzy filter is presented for fix and random-valued impulse noise. Noise detection scheme of two stages was applied to detect noise efficiently whereas for noise removal an improved Histogram based Fuzzy Color Filter (HFC) is presented. Pixels detected as noisy by the noise detection scheme are deliberated as candidate for the removal of noise. Candidate noisy pixels are then processed using a modified Histogram based Fuzzy Color Filter to estimate their non-noisy values. The idea of using multiple fuzzy membership functions is presented, so that best suitable membership function for local image statistics can be used automatically. In the proposed technique we have used three different types of fuzzy membership functions (bell-shaped, trapezoidal-shaped, and triangular-shaped) and their fuzzy number construction algorithms are proposed. Experimentation is also performed with three, five, and seven membership functions. Type and number of suitable fuzzy membership functions are then identified to remove noise. Comparison with the existing filtering techniques is established on the basis of objective quantitative measures including structural similarity index measure (SSIM) and peak-signal-to-noise-ratio (PSNR). Simulations show that this filter is superior to that of the existing state-of-the-art filtering techniques in removing fix and random-valued impulse noise whereas retaining the details of the image contents.
Authentication and copyright protection of information contents has always been a concern in prin... more Authentication and copyright protection of information contents has always been a concern in print media. The problem has become more critical with the increasing use of the Internet and digital technologies. Besides image, audio and video, the text is most extensively used medium travelling over the Internet. Digital libraries offer a quick and easy access to information such as e-books, archives, images, etc. However, making the protection of copyright is more complex and difficult. Increasing use of digital libraries, blogs and electronic commerce has made it necessary to protect digital contents. Digital watermarking came up as a solution for copyright protection problem. In this paper, we propose a novel text watermarking algorithm, which embeds the watermark image in the text (to be protected) logically using embedding algorithm and extract it later using the extraction algorithm. Experimental results demonstrate the effectiveness of the algorithm proposed in localized and dispersed attacks on the text. Objective evaluation methods like Normalized Hamming Distances (NHD), Peak-Signal-to-Noise-Ratio (PSNR), Weighted Peak-Signal-to-Noise-Ratio (WPSNR), Mean Structural Similarity Index Measures (MSSIM) and Normalized Absolute Error (NAE) metrics are used to measure the quality and similarity between original and extracted watermark images.
ABSTRACT Brain tumor is one of the major causes of death among other types of the cancers. Proper... more ABSTRACT Brain tumor is one of the major causes of death among other types of the cancers. Proper and timely diagnosis can prevent the life of a person to some extent. Therefore we have proposed an automated reliable system for the diagnosis of the brain tumor. Proposed system is a multi-stage system for brain tumor diagnosis and tumor region extraction. First, noise removal is performed as the preprocessing step on the brain MR images. Texture features are extracted from these noise free brain MR images. Next phase of the proposed system is classification that is based on these extracted features. Ensemble based SVM classification is used. More than 99% accuracy is achieved by the classification phase. After classification, proposed system extracts tumor region from tumorous images using multi-step segmentation. First step is skull removal and brain region extraction. Next step is separating tumor region from normal brain cells using FCM clustering. Results of the proposed technique show that tumor region is extracted quite accurately. This technique has been tested against the datasets of different patients received from Holy Family hospital and Abrar MRI & CT Scan center Rawalpindi.
Communications in Computer and Information Science, 2011
Global software development (GSD) outsourcing is a modern business strategy for producing high qu... more Global software development (GSD) outsourcing is a modern business strategy for producing high quality software at low cost. Most of the problems in Global software development (GSD) occur due to the lack of communication between stakeholders, time zone issues, cultural differences, etc. In this paper, our main emphasis will be to improve the Value-based requirement elicitation (VBRE) steps in GSD environment and also to overcome the major GSD environment problems while taking the process of requirement elicitation from valued stakeholders. Though this model works for every kind of project but, specifically it is good for generic software.
Proceedings of the 4th International Conference on Ubiquitous Information Technologies & Applications, 2009
Abstract: With rapid developments in the field of software products and services, it has assumed ... more Abstract: With rapid developments in the field of software products and services, it has assumed vital significance to define Value in a new perspective. With advent of new software engineering approaches like value based software engineering, this has become really relevant to ...
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Papers by Arfan Jaffar