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.
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2019, Vol. 32 
