Face Based Biometric Authentication with Changeable and Privacy Preservable Templates

Changeability, privacy protection, and verification accuracy are important factors for widespread deployment of biometrics based authentication systems. In this paper, we introduce a method for effective combination of biometrics data with user specific secret key for human verification. The proposed approach is based on discretized random orthonormal transformation of biometrics features. It provides attractive properties of zero error rate, and generates revocable and non-invertible biometrics templates. In addition, we also present another scheme where no discretization procedure is involved. The proposed methods are well supported by mathematical analysis. The feasibility of the introduced solutions on a face verification problem is demonstrated using the well known ORL and GT database. Experimentation shows the effectiveness of the proposed methods comparing with existing works.