PRIVACY PROTECTED FACE VERIFICATION SYSTEM USING SPARSE CLASSIFIER.

The demand of video surveillance has been increasing day by day; as a result the privacy protection has become a responsibility for the public as well as for legal authorities. When videos are transmitted or distributed across various public networks, the human faces should not be exposed. To deal with this problem, facial image scrambling technique appeared as a solution for privacy related applications. This paper proposes a facial verification system in the scrambled domain using sparse classifier. In the proposed method, the facial features are extracted from the scrambled faces using SIFT and LBP feature extraction methods and a T-test based feature selection method is used to select important features for classification. Then sparse representation based classifier is used for classifying the facial images. The experiments show that the proposed face verification system can meet the challenging tests in the scrambled domain.