DocumentCode
2597960
Title
A Comparison of Texture Features Based on SVM and SOM
Author
Chen, Chih-Ming ; Chen, Chien-Chang ; Chen, Chaur-Chin
Author_Institution
Dept. of Comput. Sci., Nat. TsingHua Univ., Hsinchu
Volume
2
fYear
0
fDate
0-0 0
Firstpage
630
Lastpage
633
Abstract
Experimental results of texture features derived from Gabor and other four wavelet transforms classified and clustered based on support vector machine (SVMs) and self-organizing maps (SOMs) are reported in this paper. A comparison of SVM and SOM in texture classification is illustrated. The results show that these texture sets with appropriate classifiers perform reasonably well
Keywords
image classification; image texture; self-organising feature maps; support vector machines; wavelet transforms; Gabor transforms; self-organizing maps; support vector machine; texture classification; texture features; wavelet transforms; Computer science; Data mining; Frequency; Gabor filters; Information management; Self organizing feature maps; Support vector machine classification; Support vector machines; Training data; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.51
Filename
1699284
Link To Document