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Journal of Electronic Imaging

Relative gradient local binary patterns method for face recognition under varying illuminations
Author(s): HuoRong Ren; XinXin Yan; Yan Zhou; Rui Cui; Jianwei Sun; Yang Liu
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Paper Abstract

Local binary patterns (LBPs) are effective facial texture feature descriptors in face recognition. However, the performance of original LBP-based face recognition methods rapidly deteriorates in the condition of nonmonotonic illumination variations. In order to overcome this drawback, we propose a LBP-based face recognition approach, namely relative gradient LBPs (RGLBPs), in which the relative gradient is first applied to the original face images to extract illumination invariant features. Then, an LBP describes textural and structural features for face recognition. Finally, the chi-square dissimilarity measure and the nearest neighbor classifier are used for classification. The experimental results validate that the proposed approach is efficient for the illumination problem in face recognition and also robust to expression and age variations.

Paper Details

Date Published: 8 November 2013
PDF: 6 pages
J. Electron. Imaging. 22(4) 043013 doi: 10.1117/1.JEI.22.4.043013
Published in: Journal of Electronic Imaging Volume 22, Issue 4
Show Author Affiliations
HuoRong Ren, Xidian Univ. (China)
XinXin Yan, Xidian Univ. (China)
Yan Zhou, Xidian Univ. (China)
Rui Cui, Xidian Univ. (China)
Jianwei Sun, Xidian Univ. (China)
Yang Liu, Xidian Univ. (China)

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