Combined feature selection of ReliefF-SVM RFE used in face recognition

To solve the problem that too much features have great effects on the instantaneity and accuracy of face recognition,a method named combined facial feature selection based on ReliefF-SVM RFE is proposed. The proposed method uses DCT extract facial feature and ReliefF select feature to reduce the feature dimension space initially, then uses improved SVM RFE to select optimal feature. This method solves the problem that the SVM REF feature selection consums long time because of training much features repeatedly. Finally, it uses leave-one-out method to select optimal feature subset from feature ranking table,and classification by SVM. Experiments are performed on UMIST facial database, accuracy of 98.84% is achieved when facial features are 52, recognition time only needs 0.037 s.