面向活体人脸检测的时空纹理特征级联方法

doi:10.16451/j.cnki.issn1003-6059.201902003

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Abstract To solve the security problem in identity authentication, the face liveness detection method is always employed. Therefore, a spatial-temporal texture cascaded feature method is proposed to improve the robustness of living face detection. Firstly, local binary pattern(LBP) is utilized to calculate the differential excitation of Weber local descriptor(WLD), and Prewitt operator is exploited to calculate the directional angle of WLD to extract texture features in time domain and space domain. Secondly, the histogram of texture features obtained from three orthogonal space-time planes, XY, XT and YT, is cascaded. Finally, the dynamic texture features, namely spatial-temporal texture cascade features, can be used to determine whether the real face or the disguised face. Experimental results on CASIA face anti-spoofing database and replay-attack database show that the proposed method obtains higher recognition rate than the existing mainstream local texture feature methods and it can be widely used in identity authentication and security monitoring systems.

Key words： Face Liveness Detection Local Texture Feature Dynamic Texture Feature Spatial-Temporal Texture Cascaded Feature

Received: 14 June 2018

ZTFLH:

TP 391

Fund:Supported by National Natural Science Foundation of China(No.61771347,61072127,61372193), Natural Science Foundation of Guangdong Province(No.S2013010013311,10152902001000

About author:: (GAN Junying, Ph.D., professor. Her research interests include biometric identification.) (ZHAI Yikui(Corresponding author), Ph.D., associate professor. His research interests include biometric identification and SAR image recognition.) (XIANG Li, master student. Her research interests include biometric identification.) (CAO He, master student. Her research interests include biometric identification and face beauty prediction.) (HE Guohui, Ph.D., professor. His research interests include image processing, virtual reality and multimedia information system.) (ZENG Junying, Ph.D., associate profe-ssor. His research interests include machine vision and biometrics identification.)(TAN Haiying, master student. Her research interests include biometric identification and face beauty prediction.) (DENG Wenbo, master student. His research interests include biometric identification and SAR image recognition.)

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	GAN Junying
	ZHAI Yikui
	XIANG Li
	CAO He
	HE Guohui
	ZENG Junying
	TAN Haiying
	DENG Wenbo

Cite this article:

GAN Junying,ZHAI Yikui,XIANG Li等. Spatial-Temporal Texture Cascaded Feature Method for Face Liveness Detection[J]. , 2019, 32(2): 117-123.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201902003 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I2/117

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