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