Adaptive non-local smoothing-based weberface for illumination-insensitive face recognition

Min Yao; Changming Zhu

doi:10.1117/12.2281555

21 July 2017 Adaptive non-local smoothing-based weberface for illumination-insensitive face recognition

Min Yao, Changming Zhu

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042004 (2017) https://doi.org/10.1117/12.2281555
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China

Abstract

Compensating the illumination of a face image is an important process to achieve effective face recognition under severe illumination conditions. This paper present a novel illumination normalization method which specifically considers removing the illumination boundaries as well as reducing the regional illumination. We begin with the analysis of the commonly used reflectance model and then expatiate the hybrid usage of adaptive non-local smoothing and the local information coding based on Weber’s law. The effectiveness and advantages of this combination are evidenced visually and experimentally. Results on Extended YaleB database show its better performance than several other famous methods.

Citation Download Citation

Min Yao and Changming Zhu "Adaptive non-local smoothing-based weberface for illumination-insensitive face recognition ", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042004 (21 July 2017); https://doi.org/10.1117/12.2281555

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