Image Segmentation Based on Adaptive Fuzzy-C-Means Clustering

The clustering method “Fuzzy-C-Means” (FCM) is widely used in image segmentation. However, the major drawback of this method is its sensitivity to the noise. In this paper, we propose a variant of this method which aims at resolving this problem. Our approach is based on an adaptive distance which is calculated according to the spatial position of the pixel in the image. The obtained results have shown a significant improvement of our approach performance compared to the standard version of the FCM, especially regarding the robustness face to noise and the accuracy of the edges between regions.