基于模糊聚类的图像分割研究进展

Fuzzy c-means (FCM) algorithm is a clustering process based on soft partitioning, and it has been widely used in machine learning, image processing and computer vision.Although a large number of image segmentation algorithms based on FCM have been proposed, it is still a challenge research topic to research image segmentation based on fuzzy clustering.In this paper, image segmentation algorithms based on FCM are roughly grouped into three categories: FCM algorithms based on spatial neighboring information, FCM algorithms based on histogram information, and FCM algorithms based on dimension weight.We firstly analyze and elaborate the current research on FCM algorithms.Afterwards, we analyze the performance of different algorithms according to experiments.Finally, we conclude the drawbacks of image segmentation algorithms based on FCM and the future research direction.