A face and palmprint recognition approach based on discriminant DCT feature extraction

Abstract—In the field of image processing and recognition, dis-crete cosine transform (DCT) and linear discrimination are two widely used techniques. Based on them, we present a new face and palmprint recognition approach in this paper. It first uses a two-dimensional separability judgment to select the DCT frequency bands with favorable linear separability. Then from the selected bands, it extracts the linear discriminative features by an improved Fisherface method and performs the classification by the nearest neighbor classifier. We detailedly analyze theoretical advantages of our approach in feature extraction. The experiments on face databases and palmprint database demonstrate that compared to the state-of-the-art linear discrimination methods, our approach obtains better classification performance. It can significantly im-prove the recognition rates for face and palmprint data and effec-tively reduce the dimension of feature space. Index Terms—Discrete cosine transform (DCT), DCT frequency band selection, improved Fisherface method, linear discrimination technique, two-dimensional (2-D) separability judgment. I