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
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;
Conference_Titel :
Information Science and Engineering (ISISE), 2010 International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-428-2
DOI :
10.1109/ISISE.2010.122