Face recognition using support vector machines and generalized discriminant analysis

Face recognition by machines has various important applications in our daily life. However, the task to teach machine to recognize face images has been a very challenging task. This paper presents face recognition by combining Generalized Discriminant Analysis (GDA) as a feature extractor and Support Vector Machines (SVM) as a classifier. Our experiment showed that the performance of combining these two methods as a face image classifier is better than by only using SVM. The accuracy of combined method is above 85%.