  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.
