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Journal of Electronic Imaging

Discriminant analysis with Gabor phase feature for robust face recognition
Author(s): Hong Han; Jianfei Zhu; Zhen Lei; Shengcai Liao; Stan Z. Li
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Paper Abstract

An occlusion robust image representation method is presented and applied to face recognition. In our method, Gabor phase difference representation is used mainly to resist occlusion. Based on the good ability of Gabor filters to capture image structure and the robustness to image occlusion shown here, Gabor phase features are expected to be discriminative and robust for face representation in occlusion case. Furthermore, we find that different scales and orientations of Gabor phase features lead to quite varied performance and then we analyze it carefully and find the effective Gabor phase (EGP) features. Moreover, we adopt spectral regression–based discriminant analysis, along with the extracted EGP features, to find the most discriminant subspace for classification. Thereby, an occlusion robust face image discriminant subspace is derived. Five kinds of feature representation methods and two subspace learning methods are compared for our recognition problem. Extensive experiments with various occlusion cases show the efficacy of the proposed method.

Paper Details

Date Published: 19 December 2013
PDF: 12 pages
J. Electron. Imag. 22(4) 043035 doi: 10.1117/1.JEI.22.4.043035
Published in: Journal of Electronic Imaging Volume 22, Issue 4
Show Author Affiliations
Hong Han, Xidian Univ. (China)
Jianfei Zhu, Xidian Univ. (China)
Zhen Lei, Institute of Automation (China)
Shengcai Liao, Institute of Automation (China)
Stan Z. Li, Institute of Automation (China)

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