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Papers/face anti-spoofing based on color texture analysis

face anti-spoofing based on color texture analysis

Zinelabidine Boulkenafet, Jukka Komulainen, Abdenour Hadid

2015-11-19Face Anti-SpoofingTexture Classification
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Abstract

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.

Results

TaskDatasetMetricValueModel
Depth EstimationReplay-AttackEER0.4YCbCr+HSV-LBP
Depth EstimationReplay-AttackHTER2.9YCbCr+HSV-LBP
Facial Recognition and ModellingReplay-AttackEER0.4YCbCr+HSV-LBP
Facial Recognition and ModellingReplay-AttackHTER2.9YCbCr+HSV-LBP
Visual OdometryReplay-AttackEER0.4YCbCr+HSV-LBP
Visual OdometryReplay-AttackHTER2.9YCbCr+HSV-LBP
Face ReconstructionReplay-AttackEER0.4YCbCr+HSV-LBP
Face ReconstructionReplay-AttackHTER2.9YCbCr+HSV-LBP
3DReplay-AttackEER0.4YCbCr+HSV-LBP
3DReplay-AttackHTER2.9YCbCr+HSV-LBP
3D Face ModellingReplay-AttackEER0.4YCbCr+HSV-LBP
3D Face ModellingReplay-AttackHTER2.9YCbCr+HSV-LBP
3D Face ReconstructionReplay-AttackEER0.4YCbCr+HSV-LBP
3D Face ReconstructionReplay-AttackHTER2.9YCbCr+HSV-LBP
Depth And Camera MotionReplay-AttackEER0.4YCbCr+HSV-LBP
Depth And Camera MotionReplay-AttackHTER2.9YCbCr+HSV-LBP

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