Multiscale facial structure representation for face recognition under varying illumination |
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Authors: | Taiping Zhang [Author Vitae] [Author Vitae] Yuan Yuan [Author Vitae] [Author Vitae] Zhaowei Shang [Author Vitae] [Author Vitae] Fangnian Lang [Author Vitae] |
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Affiliation: | a College of Computer Science, Chongqing University, Chongqing 400044, PR China b School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK |
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Abstract: | Facial structure of face image under lighting lies in multiscale space. In order to detect and eliminate illumination effect, a wavelet-based face recognition method is proposed in this paper. In this work, the effect of illuminations is effectively reduced by wavelet-based denoising techniques, and meanwhile the multiscale facial structure is generated. Among others, the proposed method has the following advantages: (1) it can be directly applied to single face image, without any prior information of 3D shape or light sources, nor many training samples; (2) due to the multiscale nature of wavelet transform, it has better edge-preserving ability in low frequency illumination fields; and (3) the parameter selection process is computationally feasible and fast. Experiments are carried out upon the Yale B and CMU PIE face databases, and the results demonstrate that the proposed method achieves satisfactory recognition rates under varying illumination conditions. |
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Keywords: | Illumination invariant Wavelet denoising Multiscale structure Face recognition |
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