Adaptive Filtering Fuzzy C-means Image Segmentation with Inclusion Degree

The fuzzy C-means clustering algorithm establishes the uncertain description between sample points and categories, and has the advantage of automatic image segmentation. It can effectively deal with the problems of image blur and distortion in the segmentation process, but it is sensitive to noise and segmentation results are not accurate enough. To solve this problem, this paper proposes an adaptive filtering fuzzy C-means image segmentation algorithm with inclusion degree. The algorithm has characteristics of strong anti-interference ability and high precision for segmentation. The simulation results show that the algorithm can effectively segment noise images and complex background images.