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
Subjects:	TK1-9971 Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.usm.my/46292/1/Waled%20Hussein%20Mohammed%20Al-Arashi24.pdf
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id	my-usm-ep.46292
record_format	uketd_dc
spelling	my-usm-ep.462922020-02-20T06:29:36Z Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms 2014-02 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 http://eprints.usm.my/46292/ http://eprints.usm.my/46292/1/Waled%20Hussein%20Mohammed%20Al-Arashi24.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik & Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
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
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
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
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Elektrik & Elektronik
publishDate	2014
url	http://eprints.usm.my/46292/1/Waled%20Hussein%20Mohammed%20Al-Arashi24.pdf
_version_	1747821646087979008

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

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