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Proceedings Paper

Separability oriented fusion of LBP and CS-LDP for infrared face recognition
Author(s): Zhihua Xie; Guodong Liu
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Paper Abstract

Due to low resolutions of infrared face image, the local texture features are more appreciated for infrared face feature extraction. To extract rich facial texture features, infrared face recognition based on local binary pattern (LBP) and center-symmetric local derivative pattern (CS-LDP) is proposed. Firstly, LBP is utilized to extract the first order texture from the original infrared face image; Secondly, the second order features are extracted CS-LDP. Finally, an adaptive weighted fusion algorithm based separability discriminant criterion is proposed to get final recognition features. Experimental results on our infrared faces databases demonstrate that separability oriented fusion of LBP and CS-LDP contributes complementary discriminant ability, which can improve the performance for infrared face recognition

Paper Details

Date Published: 8 October 2015
PDF: 6 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96750G (8 October 2015); doi: 10.1117/12.2197386
Show Author Affiliations
Zhihua Xie, Jiangxi Science and Technology Normal Univ. (China)
Guodong Liu, Jiangxi Science and Technology Normal Univ. (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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