关键词: 图像分割, 分水岭变换, 模糊C均值聚类, 空间信息

Abstract: In order to resolve the problems of sensitivity to noise and over-segmentation existing in traditional watershed algorithm，a new image segmentation method combined watershed translation and FCM clustering algorithm incorporating spatial information is proposed in this paper.Firstly，the median filtering is performed on the original image to simultaneously reduce noise and preserve edges.Then watershed translation is used for segmenting the image into many small regions，and a FCM clustering algorithm incorporating spatial information is proposed for merging.In the modified FCM clustering algorithm，a graph theory based metric incorporating region feature and spatial information is proposed.With the small regions as its vertices，a weighted graph is generated.The shortest paths between different vertices are calculated for measuring the distances between different regions.The experimental results show that，combining the region feature information and spatial information，the presented method gives more satisfying result than the traditional methods.

Key words: image segmentation, watershed, FCM, spatial information