CSLDA and LDA fusion based face recognition

Face recognition has great demands and become one of the most important research area of pattern recognition but there are several issues involved in it. Unsupervised statistical methods i.e. PCA, LDA, ICA are the most popular algorithms in face recognition that finds the set of basis images and rep...

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Main Authors: Razzak, M. I., Khan, M. K., Alghathbar, K., Yusof, Rubiyah
Format: Article
Language:English
Published: Wydawnictwo SIGMA - N O T Sp. z o.o. 2011
Subjects:
Online Access:http://eprints.utm.my/28819/1/RubiyahYusof2011_CsldaandLdaFusionBasedFaceRecognition.pdf
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author Razzak, M. I.
Khan, M. K.
Alghathbar, K.
Yusof, Rubiyah
author_facet Razzak, M. I.
Khan, M. K.
Alghathbar, K.
Yusof, Rubiyah
author_sort Razzak, M. I.
collection ePrints
description Face recognition has great demands and become one of the most important research area of pattern recognition but there are several issues involved in it. Unsupervised statistical methods i.e. PCA, LDA, ICA are the most popular algorithms in face recognition that finds the set of basis images and represents faces as linear combination of those images. This paper presents a novel layered face recognition method based on CSLDA and LDA. The basic aim is to decrease FAR by reducing the face dataset to very small size through layered linear discriminant analysis. Although the computational complexity at the time of recognition is much higher than conventional PCA and LDA because weights are computed for small subspace at time of recognition but it provide a good results especially for large dataset. CSLDA of LDA is insensitive to large dataset and also small sample size and it provided 84% accuracy on Banca face database. The proposed approach is also applicable on other applications and recognition methods i.e. PCA, KDA, DLDA etc.
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spelling utm.eprints-288192020-10-30T05:13:11Z http://eprints.utm.my/28819/ CSLDA and LDA fusion based face recognition Razzak, M. I. Khan, M. K. Alghathbar, K. Yusof, Rubiyah TK Electrical engineering. Electronics Nuclear engineering Face recognition has great demands and become one of the most important research area of pattern recognition but there are several issues involved in it. Unsupervised statistical methods i.e. PCA, LDA, ICA are the most popular algorithms in face recognition that finds the set of basis images and represents faces as linear combination of those images. This paper presents a novel layered face recognition method based on CSLDA and LDA. The basic aim is to decrease FAR by reducing the face dataset to very small size through layered linear discriminant analysis. Although the computational complexity at the time of recognition is much higher than conventional PCA and LDA because weights are computed for small subspace at time of recognition but it provide a good results especially for large dataset. CSLDA of LDA is insensitive to large dataset and also small sample size and it provided 84% accuracy on Banca face database. The proposed approach is also applicable on other applications and recognition methods i.e. PCA, KDA, DLDA etc. Wydawnictwo SIGMA - N O T Sp. z o.o. 2011 Article PeerReviewed application/pdf en http://eprints.utm.my/28819/1/RubiyahYusof2011_CsldaandLdaFusionBasedFaceRecognition.pdf Razzak, M. I. and Khan, M. K. and Alghathbar, K. and Yusof, Rubiyah (2011) CSLDA and LDA fusion based face recognition. Przeglad Elektrotechniczny, 87 (1). pp. 210-214. ISSN 0033-2097 http://pe.org.pl/articles/2011/1/42.pdf
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Razzak, M. I.
Khan, M. K.
Alghathbar, K.
Yusof, Rubiyah
CSLDA and LDA fusion based face recognition
title CSLDA and LDA fusion based face recognition
title_full CSLDA and LDA fusion based face recognition
title_fullStr CSLDA and LDA fusion based face recognition
title_full_unstemmed CSLDA and LDA fusion based face recognition
title_short CSLDA and LDA fusion based face recognition
title_sort cslda and lda fusion based face recognition
topic TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utm.my/28819/1/RubiyahYusof2011_CsldaandLdaFusionBasedFaceRecognition.pdf
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AT khanmk csldaandldafusionbasedfacerecognition
AT alghathbark csldaandldafusionbasedfacerecognition
AT yusofrubiyah csldaandldafusionbasedfacerecognition