Implementation of face recognition system using BioCryptosystem as template protection scheme

This paper has designed and implemented a secure face recognition system using novel Bio-Cryptographic template protection schemes. The implementation of the proposed system has been divided into three components. The face regions are detected from the input images in the first component. Then some discriminant and distinctive feature extraction techniques are applied to extract features from the facial region. In the second component, the extracted features undergo a classification task to verify or identify the person based on their face biometric. The Huffman coding technique has been incorporated with the biometric face feature as BioCryptosystem for template protection scheme in the third component. The proposed BioCryptosystem works at the feature level in two steps: dictionary-based and user-key-based approaches for encryption followed by decryption processes. During experimentation, three benchmark facial databases, CVL, CASIA-FaceV5, and FERET have been employed. The performances have been compared with some existing state-of-the-art methods concerning each database which shows the superiority of the proposed system. Moreover, some comparisons have been performed for the security analysis of the employed BioCryptosystem, which shows that the proposed system takes less time for authentication and generates longer and stronger keys than other existing Bio-cryptographic techniques.