Title :
Face recognition using fuzzy rough set and support vector machine
Author :
Wang, Shi-Yi ; Tao Liang
Author_Institution :
MOE Key Lab. of Intell. Comput. & Signal Process., Anhui Univ., Hefei, China
Abstract :
This paper proposes a method of face recognition using the support vector machine (SVM) based on the fuzzy rough set theory (FRST). Firstly, features from human face images are extracted by combining the 2-D wavelet decomposition technique with the grayscale integral projection technique. And then, the attribute reduction algorithm based on FRST is applied in face recognition. The reduction algorithm based on FRST can eliminate the redundant features of sample dataset and reduce the space dimension of the sample data. The proposed method avoids losing of information caused by dispersing before original rough set attribute reduction. Experimental results show that it can improve the classification accuracy in face recognition as compared with the method using the original rough set.
Keywords :
face recognition; feature extraction; fuzzy set theory; rough set theory; support vector machines; wavelet transforms; attribute reduction algorithm; face feature extraction; face recognition; fuzzy rough set; grayscale integral projection technique; support vector machine; wavelet decomposition technique; Face; attribute reduction; fuzzy rough set; rough set;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658621