Face recognition based on discriminant fractional Fourier feature extraction
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 1465-1471 |
Journal / Publication | Pattern Recognition Letters |
Volume | 27 |
Issue number | 13 |
Publication status | Published - 1 Oct 2006 |
Link(s)
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. © 2006 Elsevier B.V. All rights reserved.
Research Area(s)
- Angle parameter, Face recognition, Feature extraction, Fractional Fourier transform, Linear discrimination analysis, Reformative Fisherface method
Citation Format(s)
Face recognition based on discriminant fractional Fourier feature extraction. / Jing, Xiao-Yuan; Wong, Hau-San; Zhang, David.
In: Pattern Recognition Letters, Vol. 27, No. 13, 01.10.2006, p. 1465-1471.
In: Pattern Recognition Letters, Vol. 27, No. 13, 01.10.2006, p. 1465-1471.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review