Sequential Subspace Estimator for biometric authentication

In this paper, a new Sequential Subspace Estimator (SSE) algorithm for biometric authentication is proposed. In the proposed method, a sequential estimator is being designed in the image subspace which addresses the challenges due to nonlinear, nonstationary, and heterogeneous noise. Furthermore, the proposed method includes a subspace technique that overcomes the computational complexity associated with the sequential estimator. The theoretical foundation of the proposed method along with the experimental results is also presented in this paper. For the experimental evaluation of the proposed method, we use facial images from two public databases: the “Put Face Database” and the “Indian Face Database”. The experimental results demonstrate the superiority of the proposed method in comparison with its counterparts.