A novel discriminant analysis approach using angular fourier transform for face recognition

Authors:
Xiao-Yuan Jing;Lin Liu;Sheng Li;Yong-Fang Yao;Lu-Sha Bian;Qian Liu;Yong Dong;Zai-Juan Sui
Affiliations:
Nanjing University of Posts and Telecommunications;Nanjing University of Posts and Telecommunications;Nanjing University of Posts and Telecommunications;Nanjing University of Posts and Telecommunications;Nanjing University of Posts and Telecommunications;Nanjing University of Posts and Telecommunications;Nanjing University of Posts and Telecommunications;Nanjing University of Posts and Telecommunications
Venue:
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Year:
2009

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Abstract

In this paper, a novel discriminant analysis approach using Angular Fourier transform is proposed for face recognition. As a generalization of Fourier transform, the Angular Fourier transform is an important frequency-domain analysis technique. The proposed approach combines it with discriminant analysis method. First, this approach selects appropriate value of angle parameter for discrete Angular Fourier transform by using 2D separability judgment, and then it uses an improved Fisherface method to extract discriminative features from the preprocessed images. Finally, the nearest neighbor classifier is employed for classification. Using a public face databases as the test data, the experimental results demonstrate that the proposed approach outperforms several related discrimination methods.