Face Recognition Based on Support Vector Method

Support Vector Machines are a binary classification method and have demonstrated excellent results in pattern recognition. Face recognition is a multi-class problem, where the number of classes is of the known individuals. This paper we use face data extracted from Eigenfeatures and developed a method to extend SVM to using in multi-class. The training set consists of 5 images of each of the 50 persons equally distributed among frontal, approximately 15°rotated respectively, and the test set consists of 10 images each of the 50 persons. In the ICT-YCNC face gallery, the proposed system obtains competitive results highly: a correct recognition rate of 94.8% for all the 50 persons, to the less number of the persons and to the famous ORL face gallery we also get good face recognition rate.