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Papers by Somaya Al-maadeed

Research paper thumbnail of Electronic Library Institute-seerq (elisq)

Qatar Foundation Annual Research Conference, Nov 13, 2014

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Research paper thumbnail of Multi-modal biometric authentication system using face and online signature fusion

Qatar Foundation Annual Research Forum, Oct 19, 2012

Background and Objectives: There is high requirement of face and signature based multimodal biome... more Background and Objectives: There is high requirement of face and signature based multimodal biometric systems in various areas, such as banking, biometric systems and secured mobile phone operating systems. Few studies have been carried out in this area to enhance the performance of identification and authentication based on the fusion of those modalities. In multimodal biometric systems, the most common fusion approach is integration at the matching score level, but it is necessary to compare this strategy of ...

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Research paper thumbnail of Writer identification of Arabic handwriting documents using grapheme features

A system for Arabic writer identification using grapheme features and k-nearest neighbor classifi... more A system for Arabic writer identification using grapheme features and k-nearest neighbor classifier is built using Matlab programming language. The results of our preliminary study reveal that unknown writers can be identified by using edge base directional features and text-dependent method; however the simple system approach needs improvement to satisfy the requirements of real data. This project works on the following improvements: First a database of text- independent Arabic handwritten pages from around 100 different writers is gathered and used as a test bed. Then, features will be extracted from writers' handwriting. Prior to feature extraction, preprocessing operations is applied to documents to remove the background. In this research, we build an interactive background removal interface. Then the multi-scale edge-hinge features and grapheme features will be extracted from the handwritten pages. The classification will be performed by a k-nearest neighbor classifier. The project studies the performance of the new features, and recognition operations on Arabic text, on the identification rate of writers. Matlab programming language is used to write the programs for this project. This project aims at building an Arabic writer identification system consisting of three main processes: an interactive preprocessing to remove documents background, a feature extraction process to extract feature vector, and a classification process. The three processes will be implemented on the training and testing phase of the system.

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Research paper thumbnail of Recognition of off-line handwritten Arabic words using hidden Markov model approach

Hidden Markov models (HMM) have been used with some success in recognizing printed Arabic words. ... more Hidden Markov models (HMM) have been used with some success in recognizing printed Arabic words. In this paper, a complete scheme for totally unconstrained Arabic handwritten word recognition based on a model discriminant HMM is presented. A complete system able to classify Arabic handwritten words of one hundred different writers is proposed and discussed. The system first attempts to remove some of variation in the images that do not affect the identity of the handwritten word. Next, the system codes the skeleton and edge of the word so that feature information about the lines in the skeleton is extracted. Then a classification process based on the HMM approach is used. The output is a word in the dictionary. A detailed experiment is carried out and successful recognition results are reported.

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Research paper thumbnail of Writer identification using edge-based directional probability distribution features for arabic words

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Research paper thumbnail of Recognition of Off-Line Handwritten Arabic Words Using Hidden Markov Model Approach

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Research paper thumbnail of Off-line recognition of handwritten Arabic words using multiple hidden Markov models

Knowledge Based Systems, 2004

A complete scheme for unconstrained Arabic handwritten word recognition based on a multiple hidde... more A complete scheme for unconstrained Arabic handwritten word recognition based on a multiple hidden Markov models (HMM) is presented. The overall engine of this combination of a global feature scheme with a HMM module, is a system able to classify Arabic-handwritten words. The system first removes some of the variation in the images. Next, it codes the skeleton and edge of the word such that features are extracted. Then, a rule-based classifier is used as a global recognition engine. Finally, for each group, the HMM ...

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Research paper thumbnail of Automatic recognition of handwritten Arabic characters using their geometrical features

Abstract: This research aims to use geometrical features and neural networks to automatically rec... more Abstract: This research aims to use geometrical features and neural networks to automatically recognize (read) off-line handwritten Arabic words. The nature of handwritten Arabic characters and hence the problems that could be faced when automatically (optically) recognizing them are discussed. This research concentrates on the feature extraction process, ie extraction of the main geometrical features of each of the extracted handwritten Arabic characters.

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Research paper thumbnail of A new chaos-based image-encryption and compression algorithm

Abstract We propose a new and efficient method to develop secure image-encryption techniques. The... more Abstract We propose a new and efficient method to develop secure image-encryption techniques. The new algorithm combines two techniques: encryption and compression. In this technique, a wavelet transform was used to decompose the image and decorrelate its pixels into approximation and detail components. The more important component (the approximation component) is encrypted using a chaos-based encryption algorithm.

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Research paper thumbnail of Improving Prostate Cancer Classification: A Round Robin Forward Sequential Selection Approach

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Research paper thumbnail of Improving Prostate Cancer Classification: A Round Robin Forward Sequential Selection Approach

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Research paper thumbnail of Round-Robin sequential forward selection algorithm for prostate cancer classification and diagnosis using multispectral imagery

Machine Vision and …

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Research paper thumbnail of Electronic Library Institute-seerq (elisq)

Qatar Foundation Annual Research Conference, Nov 13, 2014

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Research paper thumbnail of Multi-modal biometric authentication system using face and online signature fusion

Qatar Foundation Annual Research Forum, Oct 19, 2012

Background and Objectives: There is high requirement of face and signature based multimodal biome... more Background and Objectives: There is high requirement of face and signature based multimodal biometric systems in various areas, such as banking, biometric systems and secured mobile phone operating systems. Few studies have been carried out in this area to enhance the performance of identification and authentication based on the fusion of those modalities. In multimodal biometric systems, the most common fusion approach is integration at the matching score level, but it is necessary to compare this strategy of ...

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Research paper thumbnail of Writer identification of Arabic handwriting documents using grapheme features

A system for Arabic writer identification using grapheme features and k-nearest neighbor classifi... more A system for Arabic writer identification using grapheme features and k-nearest neighbor classifier is built using Matlab programming language. The results of our preliminary study reveal that unknown writers can be identified by using edge base directional features and text-dependent method; however the simple system approach needs improvement to satisfy the requirements of real data. This project works on the following improvements: First a database of text- independent Arabic handwritten pages from around 100 different writers is gathered and used as a test bed. Then, features will be extracted from writers' handwriting. Prior to feature extraction, preprocessing operations is applied to documents to remove the background. In this research, we build an interactive background removal interface. Then the multi-scale edge-hinge features and grapheme features will be extracted from the handwritten pages. The classification will be performed by a k-nearest neighbor classifier. The project studies the performance of the new features, and recognition operations on Arabic text, on the identification rate of writers. Matlab programming language is used to write the programs for this project. This project aims at building an Arabic writer identification system consisting of three main processes: an interactive preprocessing to remove documents background, a feature extraction process to extract feature vector, and a classification process. The three processes will be implemented on the training and testing phase of the system.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Recognition of off-line handwritten Arabic words using hidden Markov model approach

Hidden Markov models (HMM) have been used with some success in recognizing printed Arabic words. ... more Hidden Markov models (HMM) have been used with some success in recognizing printed Arabic words. In this paper, a complete scheme for totally unconstrained Arabic handwritten word recognition based on a model discriminant HMM is presented. A complete system able to classify Arabic handwritten words of one hundred different writers is proposed and discussed. The system first attempts to remove some of variation in the images that do not affect the identity of the handwritten word. Next, the system codes the skeleton and edge of the word so that feature information about the lines in the skeleton is extracted. Then a classification process based on the HMM approach is used. The output is a word in the dictionary. A detailed experiment is carried out and successful recognition results are reported.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Writer identification using edge-based directional probability distribution features for arabic words

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Recognition of Off-Line Handwritten Arabic Words Using Hidden Markov Model Approach

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Off-line recognition of handwritten Arabic words using multiple hidden Markov models

Knowledge Based Systems, 2004

A complete scheme for unconstrained Arabic handwritten word recognition based on a multiple hidde... more A complete scheme for unconstrained Arabic handwritten word recognition based on a multiple hidden Markov models (HMM) is presented. The overall engine of this combination of a global feature scheme with a HMM module, is a system able to classify Arabic-handwritten words. The system first removes some of the variation in the images. Next, it codes the skeleton and edge of the word such that features are extracted. Then, a rule-based classifier is used as a global recognition engine. Finally, for each group, the HMM ...

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Research paper thumbnail of Automatic recognition of handwritten Arabic characters using their geometrical features

Abstract: This research aims to use geometrical features and neural networks to automatically rec... more Abstract: This research aims to use geometrical features and neural networks to automatically recognize (read) off-line handwritten Arabic words. The nature of handwritten Arabic characters and hence the problems that could be faced when automatically (optically) recognizing them are discussed. This research concentrates on the feature extraction process, ie extraction of the main geometrical features of each of the extracted handwritten Arabic characters.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A new chaos-based image-encryption and compression algorithm

Abstract We propose a new and efficient method to develop secure image-encryption techniques. The... more Abstract We propose a new and efficient method to develop secure image-encryption techniques. The new algorithm combines two techniques: encryption and compression. In this technique, a wavelet transform was used to decompose the image and decorrelate its pixels into approximation and detail components. The more important component (the approximation component) is encrypted using a chaos-based encryption algorithm.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Improving Prostate Cancer Classification: A Round Robin Forward Sequential Selection Approach

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Improving Prostate Cancer Classification: A Round Robin Forward Sequential Selection Approach

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Round-Robin sequential forward selection algorithm for prostate cancer classification and diagnosis using multispectral imagery

Machine Vision and …

Bookmarks Related papers MentionsView impact