Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13797
Title: Pseudo-Gabor wavelet for face recognition
Authors: Xie, X
Liu, W
Lam, KM 
Issue Date: 2013
Publisher: Is&T & Spie
Source: Journal of electronic Imaging, 2013, v. 22, no. 2, 23029 How to cite?
Journal: Journal of Electronic Imaging 
Abstract: An efficient face-recognition algorithm is proposed, which not only possesses the advantages of linear subspace analysis approaches-such as low computational complexity-but also has the advantage of a high recognition performance with the waveletbased algorithms. Based on the linearity of Gabor-wavelet transformation and some basic assumptions on face images, we can extract pseudo-Gabor features from the face images without performing any complex Gabor-wavelet transformations. The computational complexity can therefore be reduced while a high recognition performance is still maintained by using the principal component analysis (PCA) method. The proposed algorithm is evaluated based on the Yale database, the Caltech database, the ORL database, the AR database, and the Facial Recognition Technology database, and is compared with several different face recognition methods such as PCA, Gabor wavelets plus PCA, kernel PCA, locality preserving projection, and dual-tree complex wavelet transformation plus PCA. Experiments show that consistent and promising results are obtained.
URI: http://hdl.handle.net/10397/13797
ISSN: 1017-9909
DOI: 10.1117/1.JEI.22.2.023029
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