Affine Normalized Krawtchouk Moments Based Face Recognition

In this paper, we have developed a new local descriptor based on Krawtchouk polynomial moments. The interest points are initially detected using the Canny edge detector and made the region around each interest point scale and affine normalized. The region is then represented using Krawtchouk polynomial and hence formed the descriptor. Experiments have been conducted keeping the face recognition problem in focus. By using the sparse representation concept, classification of face images is done. Experimental results on the ORL dataset and a subset of pose and illumination variant FERET dataset have shown the classification capability of our descriptor for face recognition applications.