A Novel Approach to Generate Face Biometric Template Using Binary Discriminating Analysis

In identity management system, commonly used biometric recognition system needs attention towards issue of biometric template protection as far as more reliable solution is concerned. In view of this biometric template protection algorithm should satisfy security, discriminability and cancelability. As no single template protection method is capable of satisfying the basic requirements, a novel technique for face biometric template generation and protection is proposed. The novel approach is proposed to provide security and accuracy in new user enrolment as well as verification process. This novel technique takes advantage of both the hybrid approach and the binary discriminant analysis algorithm. This algorithm is designed on the basis of random projection, binary discriminant analysis and fuzzy commitment scheme. Three publicly available benchmark face databases (FERET, FRGC, CMU-PIE) are used for evaluation. The proposed novel technique enhances the discriminability and recognition accuracy in terms of matching score of the face images and provides high security. This paper discusses the corresponding results.

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