Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms

Automatic face recognition has been a focus research topic in past few decades. This is due to the advantages of face recognition and the potential need for high security in commercial and law enforcement applications. However, due to nature of the face, it is subjected to several variations. Thus,...

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Main Author: Al-Arashi, Waled Hussein Mohammed
Format: Thesis
Language:English
Published: 2014
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Online Access:http://eprints.usm.my/46292/1/Waled%20Hussein%20Mohammed%20Al-Arashi24.pdf
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spelling my.usm.eprints.46292 http://eprints.usm.my/46292/ Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms Al-Arashi, Waled Hussein Mohammed TK1-9971 Electrical engineering. Electronics. Nuclear engineering Automatic face recognition has been a focus research topic in past few decades. This is due to the advantages of face recognition and the potential need for high security in commercial and law enforcement applications. However, due to nature of the face, it is subjected to several variations. Thus, finding a good face recognition system is still an active research field till today. Many approaches have been proposed to overcome the face variations. In the midst of these techniques, subspace methods are considered the most popular and powerful techniques. Among them, eigenface or Principal Component Analysis (PCA) method is considered as one of the most successful techniques in subspace methods. One of the most important extensions of PCA is Two-dimensional PCA (2DPCA). However, 2DPCA-based features are matrices rather than vectors as in PCA. Hence, different distance computation methods have been proposed to calculate the distance between the test feature matrix and the training feature matrices. All previous methods deal with the classification problem mathematically without any consideration between feature matrices and the face images. Besides, the system performance in practical applications relies on the number of eigenvectors chosen. As a solution to the above mentioned issues, four new distance methods have been proposed in this thesis, which are based on the rows of a feature matrix of 2DPCA-based algorithms. Through experiments, using eight face databases, their improvements compared to the previous distance methods are demonstrated. 2014-02 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/46292/1/Waled%20Hussein%20Mohammed%20Al-Arashi24.pdf Al-Arashi, Waled Hussein Mohammed (2014) Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms. PhD thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic TK1-9971 Electrical engineering. Electronics. Nuclear engineering
spellingShingle TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Al-Arashi, Waled Hussein Mohammed
Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms
description Automatic face recognition has been a focus research topic in past few decades. This is due to the advantages of face recognition and the potential need for high security in commercial and law enforcement applications. However, due to nature of the face, it is subjected to several variations. Thus, finding a good face recognition system is still an active research field till today. Many approaches have been proposed to overcome the face variations. In the midst of these techniques, subspace methods are considered the most popular and powerful techniques. Among them, eigenface or Principal Component Analysis (PCA) method is considered as one of the most successful techniques in subspace methods. One of the most important extensions of PCA is Two-dimensional PCA (2DPCA). However, 2DPCA-based features are matrices rather than vectors as in PCA. Hence, different distance computation methods have been proposed to calculate the distance between the test feature matrix and the training feature matrices. All previous methods deal with the classification problem mathematically without any consideration between feature matrices and the face images. Besides, the system performance in practical applications relies on the number of eigenvectors chosen. As a solution to the above mentioned issues, four new distance methods have been proposed in this thesis, which are based on the rows of a feature matrix of 2DPCA-based algorithms. Through experiments, using eight face databases, their improvements compared to the previous distance methods are demonstrated.
format Thesis
author Al-Arashi, Waled Hussein Mohammed
author_facet Al-Arashi, Waled Hussein Mohammed
author_sort Al-Arashi, Waled Hussein Mohammed
title Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms
title_short Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms
title_full Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms
title_fullStr Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms
title_full_unstemmed Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms
title_sort towards practical face recognition system employing row-based distance method in 2dpca based algorithms
publishDate 2014
url http://eprints.usm.my/46292/1/Waled%20Hussein%20Mohammed%20Al-Arashi24.pdf
http://eprints.usm.my/46292/
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score 13.211869