关键词: 多目标进化算法, 核聚类, 图像分割, 分水岭

Abstract: The traditional clustering-based image segmentation generally only utilizes the gray information of the image. In order to better use the region and edge information, a multi-objective fuzzy kernel clustering image segmentation algorithm based on watershed over-segmentation is proposed. The watershed method is used to over-segment the image and obtain some regions. Then the multi-objective fuzzy kernel clustering algorithm is used to cluster the representative points of the regions and the pixels on watershed. All the pixels of the image are labeled according to the clustering results of the region and the watershed to obtain the final image segmentation result. The experimental results show that the objective in the image can be more completely segmented from the background due to using the image region information.

Key words: multi-objective evolutionary algorithm, kernel clustering, image segmentation, watershed