Face Recognition Based on Discrete Cosine Transform and Support Vector Machine

Face recognition is a rapidly growing research area due to the increasing demands for the security in commercial and jurally enforcement applications. High information redundancy and correlation in face images result in the inefficiency when such images are used directly for recognition. In this paper, discrete cosine transforms is used to reduce image information redundancy, because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. The experimental results on the ORL face database utilizing the SVM algorithm show that the satisfying recognition performance can be obtained. The correct recognition rate is 96.5%.