Abstract:

When traditional FCM（Fuzzy C-Means) clustering algorithm applied to image segmentation, because of not combining with image spatial information, it is sensitive to noise, can not produce ideal image segmentation. An improved FCM algorithm based on neighboring membership constraint for image segmentation is proposed, which improves the robustness of image noise through adding the neighborhood spatial information to FCM objective function to constrain the membership function. The results of segmentation are expected. Experimental results indicate that this algorithm has a strong ability to inhibit noise, and can get better segmentation effectiveness.

Key words: fuzzy C-means(FCM), image segmentation, spatial neighboring information, noise