Face recognition based on singular-value feature vectors

Quan Pan; Min-Gui Zhang; De-Long Zhou; Yong-Mei Cheng; Hong-Cai Zhang

doi:10.1117/1.1588299

1 August 2003 Face recognition based on singular-value feature vectors

Quan Pan, Min-Gui Zhang, De-Long Zhou, Yong-Mei Cheng, Hong-Cai Zhang

Optical Engineering, Vol. 42, Issue 8, (August 2003). https://doi.org/10.1117/1.1588299

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.

©(2003) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Quan Pan, Min-Gui Zhang, De-Long Zhou, Yong-Mei Cheng, and Hong-Cai Zhang "Face recognition based on singular-value feature vectors," Optical Engineering 42(8), (1 August 2003). https://doi.org/10.1117/1.1588299

Published: 1 August 2003

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