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Face anti-spoofing using Haralick features
2016
2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)
Face spoofing can be performed in a variety of ways such as replay attack, print attack, and mask attack to deceive an automated recognition algorithm. To mitigate the effect of spoofing attempts, face anti-spoofing approaches aim to distinguish between genuine samples and spoofed samples. The focus of this paper is to detect spoofing attempts via Haralick texture features. The proposed algorithm extracts block-wise Haralick texture features from redundant discrete wavelet transformed frames
doi:10.1109/btas.2016.7791171
dblp:conf/btas/AgarwalSV16
fatcat:em3ruijx5ncuxhmpc4wv3wpxre