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Proceedings Paper

Adaptive non-local smoothing-based weberface for illumination-insensitive face recognition
Author(s): Min Yao; Changming Zhu
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Paper 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.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042004 (21 July 2017); doi: 10.1117/12.2281555
Show Author Affiliations
Min Yao, Shanghai Maritime Univ. (China)
Changming Zhu, Shanghai Maritime Univ. (China)

Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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