为了解决图像分割中容易出现的过分割问题，提出了一种基于图的彩色图像分割算法． 该算法在区域合并的基础上，首先用Mean shift 方法进行预处理，得到初始过分
割区域后对其构造邻接图，然后计算邻接区域的颜色、纹理及边缘特征相似性以判断区域是否需要合并直到所有满足条件的区域都被合并． 为了保持图像的全局属性，文中通过查找最优合并成本的方式进行区域合并． 实验结果表明: 即使在图像目标和背景区域颜色比较相似时，文中算法也能较好地实现对目标区域的完整分割; 与其他4 种算法相比，文中算法具有更好的分割性能．

In order to solve the over-segmentation problem in the image segmentation,a graph-based color image segmentation algorithm is proposed.In the algorithm,on the basis of the region-merging method,the over-segmentation regions are obtained by using Mean shift to preprocess an image,and for the over-segmentation regions,a region adjacency graph is constructed.Then,the color,texture and edge contour similarities between adjacency regions are measured to judge if adjacency regions need to be merged,until all the satisfactory regions are merged.Besides,the regions are merged by searching the optimal merging-cost,so as to preserve some global prosperity of the image.Experimental results indicate that the proposed algorithm can completely segment object regions even when the color features between background regions and object regions of an image are similar,and it has a better segmentation performance in comparison with four state-of-the-art segmentation algorithms.