Face anti-spoofing based on sharpness profiles

Natural images particularly connected with portraits exhibit a diversity in the sharpness profile commensurate with varying depth associated with different parts of the face. This depth variation puts the object (the 3D face) slightly out of focus in different parts of the image. When a secondary image is created from this portrait, this blurring effect is amplified particularly if the plane of the printed photo is not aligned with the object plane of focus. Thus photos of photos exhibit greater homogeneity in the sharpness profiles and have overall lower sharpness values than their natural counterparts. This principle has been demonstrated through a lens model and has been applied towards face anti-spoofing. Proposed system was tested on the CASIA dataset and showed a recognition rate of 98.38% corresponding to a false positive rate of 10%.

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