Abstract
How to efficiently utilize the color image information and extract effective features is the key of color face recognition. In this paper, we first analyze the similarities between facial color component image samples and their influence on color face recognition. Then we propose a novel color face recognition approach named within-component and between-component discriminant analysis (WBDA), which realizes discriminant analysis not only within each color component but also between different components. Experimental results on the face recognition grand challenge (FRGC) version 2 database demonstrate that the proposed approach outperforms several representative color face recognition methods.
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