A Novel Approach For Generating Face Template Using Bda
This work addresses biometric template security and accuracy for identity management systems, representing an incremental improvement through a hybrid method.
The paper tackles the problem of biometric template protection in face recognition systems by proposing a hybrid approach combining random projection, binary discriminant analysis, and fuzzy commitment schemes. The result shows an 80% enhancement in discriminability and recognition accuracy in matching scores across three benchmark face databases while providing high security.
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 template generation and protection is proposed. The novel approach is proposed to provide security and accuracy in new user enrollment as well as authentication 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 are used for evaluation. The proposed novel technique enhances the discriminability and recognition accuracy by 80% in terms of matching score of the face images and provides high security.