Illumination-invariant face identification using edge-based feature vectors in pseudo-2D Hidden Markov Models

A pseudo-2D Hidden Markov Model-based face identification system employing the edge-based feature representation has been developed. In the HMM-based face recognition algorithms, 2D discrete cosine transform (DCT) is often used for generating feature vectors. However, DCT-based feature representations are not robust against the variation in illumination changes. In order to enhance the robustness against illumination conditions, the edge-based feature representation has been employed. This edge-based feature representation has already been applied to robust face detection in our previous work and is compatible to processing in the dedicated VLSI hardware system which we have developed for real-time performance. The robustness against illumination change of the pseudo-2D HMM-based face identification system has been demonstrated using both the AT&T face database and the Yale face database B.