Research on face spoofing detection has mainly been focused on analyzing the luminance of the face images, hence discarding the chrominance information which can be useful for discriminating fake faces from genuine ones. In this work, we propose a new face anti-spoofing method based on color texture analysis. We analyze the joint color-texture information from the luminance and the chrominance channels using a color local binary pattern descriptor. More specifically, the feature histograms are extracted from each image band separately. Extensive experiments on two benchmark datasets, namely CASIA face anti-spoofing and Replay-Attack databases, showed excellent results compared to the state-of-the-art. Most importantly, our inter-database evaluation depicts that the proposed approach showed very promising generalization capabilities.
In the work REF , Boulkenafet et al. analyze the joint color-texture information from the luminance and the chrominance channels using a color local binary pattern descriptor and showed excellent results according to their experimental results.
Face anti-spoofing based on color texture analysis
2015 IEEE International Conference on Image Processing (ICIP)
2015 IEEE International Conference on Image Processing (ICIP)
Computer Science