Statistic feature-based scheme for the template protection of 3D face recognition

The security of biometric template is an important factor in a biometric system's security. In a traditional biometric system, the template being saved directly in a reference database results in a series of security and privacy risks, which limits the development of biometric recognition technique. This paper provides a template protection scheme that is suit for statistic feature-based algorithm, which is widely used in face recognition. The core idea of the scheme is the match between template and measured feature by using Hash function. The scheme merges of three methods, which are selecting primary components, quantization and error correction coding, to eliminate the contradiction between the fuzziness of the biometric information and the sensitiveness of the hash function. The proposed scheme has been applied to 3D face recognition, the analysis demonstrated the security of the scheme and the simulation results showed the feasibility of the scheme.