A Novel Discriminant Analysis Approach Using Angular Fourier Transform for Face Recognition

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 ana...

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Bibliographic Details
Main Authors: Xiaoyuan Jing, Lin Liu, Sheng Li, Yongfang Yao, Lusha Bian, Qian Liu, Yong Dong, Zaijuan Sui
Format: Conference Proceeding
Language:English
Subjects:
angle parameter
Angular Fourier transform
Data mining
Face recognition
Feature extraction
Fourier transforms
Frequency domain analysis
Image analysis
Image databases
improved Fisherface method
Information analysis
Nearest neighbor searches
Signal processing
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Summary: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.
DOI:10.1109/IITA.2009.100