DocumentCode
3446082
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
Volume
2
fYear
2010
fDate
29-31 Oct. 2010
Firstpage
777
Lastpage
779
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location
Xiamen
Print_ISBN
978-1-4244-6582-8
Type
conf
DOI
10.1109/ICICISYS.2010.5658621
Filename
5658621
Link To Document