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| Face Recognition under Complex Illumination Based on Multi-scale Weberface and Gradientface |
| CHENG Shu-hong,LIU Jie |
| Institute of Electrical Engineering, the Key Lab of Measurement Technology and Instrumentation of Hebei Province,Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract Aiming at the problem of the effect of Complex Illumination on face recognition rates, an integrated method based multi-scale Weber-face and gradient-face is proposed. The method starts with defining the multi-scale Weber-face, which can effectively describe the face texture structure and reduce the influence of different lighting to some extent. Then multiscale face and GF are fused to extract the face illumination invariant. Finally, multi-class support vector machine is employed for face authentication. The experiments are executed both on CMU-PIE and Yale B face databases. The experimental results have indicated that the proposed method can effectively eliminate the influence of face recognition under complex illumination and the recognition rates are superior to Weber-face, multiscale Weber-face and gradient-face, even single sample images with serious light as training sample images can also work well.
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Received: 10 June 2015
Published: 28 December 2016
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Corresponding Authors:
CHENG Shuhong
E-mail: shhcheng@ysu.edu.cn
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2017, Vol. 38 
