Face Recognition Based on Binary Edge Map and Support Vector Machine

In this paper, a novel face recognition scheme is presented. Our method uses binary edge map (BEM) as face representation and employs support vector machine (SVM) as face classifiers. The BEM is extracted using locally adaptively threshold (LAT) method. Experimental results show that a face recognition rate of 92.73% can be achieved on 165 Yale face images and 95.62% can be achieved on 798 AR images, indicating that the proposed approach is robust to lighting changes.