Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13147
Title: Face recognition based on discriminant fractional Fourier feature extraction
Authors: Jing, XY
Wong, HS
Zhang, D 
Keywords: Angle parameter
Face recognition
Feature extraction
Fractional Fourier transform
Linear discrimination analysis
Reformative Fisherface method
Issue Date: 2006
Publisher: North-Holland
Source: Pattern recognition letters, 2006, v. 27, no. 13, p. 1465-1471 How to cite?
Journal: Pattern recognition letters 
Abstract: Developed from the conventional Fourier transform, the fractional Fourier transform is a powerful signal analysis and processing technique. In this paper, we apply it to the field of face recognition. By combining it with the discrimination analysis technique, we propose a new face recognition approach. First, we use a two-dimensional separability judgment to select appropriate value of angle parameter for discrete fractional Fourier transform. Second, we present a reformative Fisherface method to extract discriminative features from the preprocessed images and perform the classification using the nearest neighbor classifier. Experimental results on two public face databases indicate that our approach outperforms four representative discrimination methods. It obtains better and robust classification effects.
URI: http://hdl.handle.net/10397/13147
ISSN: 0167-8655
EISSN: 1872-7344
DOI: 10.1016/j.patrec.2006.02.020
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