Face recognition using DCT-based feature vectors

Face recognition has many applications ranging from security access to video indexing by content. We describe an automatic face recognition system which is VQ-based and examine the effects of feature selection, feature dimensionality and codebook size on recognition performance in the VQ framework. In particular, we examine DCT-based feature vectors in such a system. DCT-based feature vectors have the additional appeal that the recognition can be performed directly on the bitstream of compressed images which are DCT-based. The system described consists of three parts: a preprocessing step to segment the face, the feature selection process and the classification. Recognition rates for a database of 500 images shows promising results.