Color face recognition based on statistically orthogonal analysis of projection transforms

Authors:
Jiangyue Man;Xiaoyuan Jing;Qian Liu;Yongfang Yao;Kun Li;Jingyu Yang
Affiliations:
College of Automation, Nanjing University of Posts and Telecommunications, China;College of Automation, Nanjing University of Posts and Telecommunications, China and State Key Laboratory of Software Engineering, Wuhan University, China and State Key Laboratory for Novel Softwa ...;College of Automation, Nanjing University of Posts and Telecommunications, China;College of Automation, Nanjing University of Posts and Telecommunications, China;College of Automation, Nanjing University of Posts and Telecommunications, China;College of Computer Science, Nanjing University of Science and Technology, China
Venue:
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Year:
2011

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Abstract

In this paper, we propose a novel color face feature extraction approach named statistically orthogonal analysis (SOA). It in turn calculates the projection transforms of the red, green and blue color component image sets by using the Fisher criterion, and simultaneously makes the obtained transforms mutually statistically orthogonal. SOA can enhance the complementation and remove the correlation between discriminant features separately extracted from three color component image sets. Experimental results on the AR and FRGC version 2 color face image databases demonstrate that SOA achieves better recognition results than several related color face recognition methods.