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Received: 2004-01-27

Revision Accepted: 2004-08-06

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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.5 P.454-459

http://doi.org/10.1631/jzus.2005.A0454


A novel face recognition method with feature combination


Author(s):  LI Wen-shu, ZHOU Chang-le, XU Jia-tuo

Affiliation(s):  School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   store6@163.com

Key Words:  Fisher discriminant criterion, Face recognition (FR), Linear discriminant analysis (LDA), Principal component analysis (PCA), Small sample size (SSS)


LI Wen-shu, ZHOU Chang-le, XU Jia-tuo. A novel face recognition method with feature combination[J]. Journal of Zhejiang University Science A, 2005, 6(5): 454-459.

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DOI - 10.1631/jzus.2005.A0454


Abstract: 
A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix effectively, and Global feature vectors (PCA-transformed) and local feature vectors (Gabor wavelet-transformed) are integrated by complex vectors as input feature of improved LDA. The proposed method is compared to other commonly used FR methods on two face databases (ORL and UMIST). Results demonstrated that the performance of the proposed method is superior to that of traditional FR approaches.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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