Face Recognition using a Cognitive Processing Model

In the conventional eigenface method, the principle component analysis (PCA) algorithm associates the eigen vectors with the changes in illumination. In this paper, we propose an improvement of facial image association for face recognition using a cognitive processing model. This method is based on the notion of multiple-phase associative memory. The Essex face database is used to verify our model for facial image recognition and compare the results of face recognition with conventional eigenface method. The simulation results show that the proposed cognitive processing model approach results in better performance than that of the conventional eigenface approach; while the computational complexity remains of the same magnitude as that of the eigenface method.