Title :
A New Approach for Face Recognition Based on SGFS and SVM
Author :
Wang, Li ; Sun, Yunlian
Author_Institution :
Sch. of Electr. Eng., Wuhan Univ., Wuhan
Abstract :
A new face recognition method based on the simple gabor feature space(SGFS) and support vector machine (SVM) is presented here. Firstly, the key points of face image were filtered by the Gabor filter bank to obtain the SGFS feature matrices. Secondly the SGFS feature matrices were combined together to establish the face simple Gabor feature, representing the face. Finally, the SVM classifier was built to classify the face simple Gabor feature to realize the face recognition. The Experiment results based on ORL database show that, this method has small mount of key feature point, the max recognition rate is 95% and it is feasibale.
Keywords :
Gabor filters; face recognition; support vector machines; Gabor filter bank; classifiers; face image; face recognition; simple Gabor feature space; support vector machine; Face recognition; Feature extraction; Filter bank; Frequency; Gabor filters; Humans; Image recognition; Independent component analysis; Support vector machine classification; Support vector machines;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on
Conference_Location :
Wuhan
Print_ISBN :
1-4244-1120-3
DOI :
10.1109/ICBBE.2007.138