One Rough Intuitionistic Type-2 FCM Algorithm for Image Segmentation

Zhong-qiang PAN, Di LI, Xiang-jian CHEN


In recent years, the segmentation of images now is confronted with presence of uncertainty and noise. Because the fuzzy clustering algorithm is not very effective in noise processing and the accuracy of image segmentation is not high enough. So one hybrid clustering algorithm combined with intuitionistic fuzzy factor and local spatial information is proposed. Experimental results show that the proposed algorithm is superior to other methods in image segmentation accuracy and improves the robustness of the algorithm. In noise image segmentation, noise interference is better suppressed.


Intuitionistic type-2 fuzzy, Image segmentation, Rough sets, Intuitionistic type-2 fuzzy c-means clustering


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