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Relative gradient local binary patterns method for face recognition under varying illuminations

[+] Author Affiliations
Ren HuoRong

Xidian University, School of Electro-Mechanical Engineering, No. 2, South TaiBai Road, Xi’an 710071, China

Yan XinXin

Xidian University, School of Electro-Mechanical Engineering, No. 2, South TaiBai Road, Xi’an 710071, China

Zhou Yan

Xidian University, School of Electro-Mechanical Engineering, No. 2, South TaiBai Road, Xi’an 710071, China

Cui Rui

Xidian University, School of Electro-Mechanical Engineering, No. 2, South TaiBai Road, Xi’an 710071, China

Sun JianWei

Xidian University, School of Electro-Mechanical Engineering, No. 2, South TaiBai Road, Xi’an 710071, China

Liu Yang

Xidian University, School of Electro-Mechanical Engineering, No. 2, South TaiBai Road, Xi’an 710071, China

J. Electron. Imaging. 22(4), 043013 (Nov 08, 2013). doi:10.1117/1.JEI.22.4.043013
History: Received December 16, 2012; Revised September 10, 2013; Accepted October 1, 2013
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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.

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Citation

Ren HuoRong ; Yan XinXin ; Zhou Yan ; Cui Rui ; Sun JianWei, et al.
"Relative gradient local binary patterns method for face recognition under varying illuminations", J. Electron. Imaging. 22(4), 043013 (Nov 08, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.4.043013


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