Separability oriented fusion of LBP and CS-LDP for infrared face recognition

Zhihua Xie; Guodong Liu

doi:10.1117/12.2197386

8 October 2015 Separability oriented fusion of LBP and CS-LDP for infrared face recognition

Zhihua Xie, Guodong Liu

Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 96750G (2015) https://doi.org/10.1117/12.2197386
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China

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

Citation Download Citation

Zhihua Xie and Guodong Liu "Separability oriented fusion of LBP and CS-LDP for infrared face recognition", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96750G (8 October 2015); https://doi.org/10.1117/12.2197386

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