DocumentCode :
2121260
Title :
Robust Image Segmentation Algorithm Based on Rough Sets and Fuzzy C-Means
Author :
Chao-quan, Zhang ; Jian-Sheng, Liu ; Wei-Gang, Zou
Author_Institution :
Fac. of Sci., Jiangxi Univ. of Sci. & Technol., Ganzhou, China
fYear :
2010
fDate :
24-26 Dec. 2010
Firstpage :
481
Lastpage :
484
Abstract :
Image segmentation with the traditional Fuzzy C-means (FCM) algorithm only uses each pixel´s gray value, when the image is corrupted by noises, the accuracy of segmentation will be greatly reduced. So, this paper proposed an image segmentation method which based on rough sets theory and fuzzy c-mean clustering. The test result shows that the method has a good segmentation performance.
Keywords :
fuzzy set theory; image denoising; image segmentation; pattern clustering; rough set theory; FCM algorithm; fuzzy c-mean clustering; image denoising; image segmentation; rough sets theory; Accuracy; Clustering algorithms; Image segmentation; Noise; Noise measurement; Partitioning algorithms; Pixel; cluster; fuzzy c-means; image segmentation; rough sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ISISE), 2010 International Symposium on
Conference_Location :
Shanghai
ISSN :
2160-1283
Print_ISBN :
978-1-61284-428-2
Type :
conf
DOI :
10.1109/ISISE.2010.122
Filename :
5945151
Link To Document :
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