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Optical Engineering

Face recognition based on singular-value feature vectors
Author(s): Quan Pan; Min-Gui Zhang; De-Long Zhou; Yong-Mei Cheng; Hong-Cai Zhang
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Paper Abstract

Automatic human face recognition is a difficult but significant problem. A method for face recognition based on singular-value feature vectors is discussed. Three algorithms of face recognition based on singular-value feature vectors are proposed. These algorithms are face recognition using principal component analysis based on singular-value feature vectors, face recognition by Fisher linear discriminant analysis based on singular-value feature vectors, and face recognition using the discriminant Karhunen Loeve (DKL) transform based on singular-value feature vectors. Experimental results show that face recognition based on singular-value feature vectors is effective.

Paper Details

Date Published: 1 August 2003
PDF: 7 pages
Opt. Eng. 42(8) doi: 10.1117/1.1588299
Published in: Optical Engineering Volume 42, Issue 8
Show Author Affiliations
Quan Pan, Northwest Polytechnical Univ. (China)
Min-Gui Zhang, Northwest Polytechnical Univ. (China)
De-Long Zhou, Institute of Computing Technology (China)
Yong-Mei Cheng, Northwestern Polytechnical Univ. (China)
Hong-Cai Zhang, Northwest Polytechnical Univ. (China)


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