DocumentCode :
2878783
Title :
Algorithm of Texture Segmentation Combining FCM and FSVM
Author :
Liu, Lu ; Wang, Tai-Yong
Author_Institution :
Sch. of Precision Instrum. & Opto-Electron. Eng., Tianjin Univ., Tianjin, China
fYear :
2009
fDate :
1-3 Nov. 2009
Firstpage :
294
Lastpage :
297
Abstract :
Fuzzy support vector machine(FSVM), as a improved support vector machine(SVM), is a powerful classifier in texture image segmentation because of its outstanding performance in high-dimensional classification. However, FSVM, as a supervised classification algorithm, is unable to classify the features of the texture image automatically because training data are needed. To solve this problem, a texture segmentation algorithm combing the fuzzy C-means clustering algorithm(FCM) and FSVM is proposed. The FCM provides training data and automatic texture segmentation is carried out. Experiments based on Matlab 7.0 are carried through, and this algorithm has presented its validity in improving segmentation precision.
Keywords :
fuzzy set theory; image classification; image segmentation; image texture; pattern clustering; support vector machines; Matlab 7.0; SVM; fuzzy C-means clustering algorithm; fuzzy support vector machine; image classification; texture image segmentation; Clustering algorithms; Fuzzy sets; Image segmentation; Intelligent networks; Kernel; Pixel; Rough sets; Support vector machine classification; Support vector machines; Training data; fuzzy C-means; fuzzy support vector machine; texture segmentation; wavelet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
Type :
conf
DOI :
10.1109/ICINIS.2009.81
Filename :
5367117
Link To Document :
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