Infrared face recognition based on binary particle swarm optimization and SVM-wrapper model

Zhihua Xie; Guodong Liu

doi:10.1117/12.2197388

15 October 2015 Infrared face recognition based on binary particle swarm optimization and SVM-wrapper model

Zhihua Xie, Guodong Liu

Proceedings Volume 9674, AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology; 96740J (2015) https://doi.org/10.1117/12.2197388
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China

Abstract

Infrared facial imaging, being light- independent, and not vulnerable to facial skin, expressions and posture, can avoid or limit the drawbacks of face recognition in visible light. Robust feature selection and representation is a key issue for infrared face recognition research. This paper proposes a novel infrared face recognition method based on local binary pattern (LBP). LBP can improve the robust of infrared face recognition under different environment situations. How to make full use of the discriminant ability in LBP patterns is an important problem. A search algorithm combination binary particle swarm with SVM is used to find out the best discriminative subset in LBP features. Experimental results show that the proposed method outperforms traditional LBP based infrared face recognition methods. It can significantly improve the recognition performance of infrared face recognition.

Citation Download Citation

Zhihua Xie and Guodong Liu "Infrared face recognition based on binary particle swarm optimization and SVM-wrapper model", Proc. SPIE 9674, AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology, 96740J (15 October 2015); https://doi.org/10.1117/12.2197388

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