Research of face recognition using wavelet and SVM
This work was supported by the State 863 Program (2003AA148040), the National Natural Science Foundation of China (grant number 10471151,60216263, 6990312), New Century Excellent Talent Support Project of Chinese Ministry of Education, Doctor Station Foundation of Chinese Ministry of Education, Chongqing Tackle Key Problem Program and Chongqing Natural Science Foundation.
Face recognition is a rapidly growing research area due to it is contactless, most natural and most humanized. Many issues needed to do research exist in face recognition. A novel wavelet-based and SVM framework for face training and recognizing is proposed. FMT and PCA are also used for improving the accuracy and performance. In order for searching for the best performance, many experiments conducted with this method show that face recognition is largely affected by wavelet decomposing level, and at the same time by SVM type and kernel. So for high recognizing accuracy, proper methods and parameters are needed. The results prove that our scheme is an efficient method as 2D facial image recognition.
