Feature extraction using discrete cosine transform for face recognition

A simple statistical analysis has been used to select the discriminant coefficients of the discrete cosine transform for the face recognition. The proposed procedure is different from the traditional zigzag or zonal masking. It searches for coefficients which have more ability to discriminate different classes better than other coefficients. Also the extensive span of DCT coefficients has been concerned in our proposed algorithm. Various coefficient selection algorithms have been compared. Simulation results on the ORL and Yale face database show the success of the proposed approach.