The invention discloses an image segmentation method fusing color and depth information. According to the method, firstly, a meanshift algorithm is used for segmenting an input color image to obtain an over-segmentation region set, and then similarities among all the regions are calculated and include color similarities, depth similarities and fusions of the color similarities and the depth similarities; then according to a depth image, seed regions of a target and seed regions of a background are automatically selected; finally, an MSRM algorithm is used for merging the regions, so that a final segmentation result is obtained. In the process of calculating the similarities among the regions, the color information is used, besides, the depth information is dynamically fused, and the problem that when the target color and the background color are similar, and namely a long-scale contrast edge exists between objects, correct segmentation can not be achieved is solved. The seed regions are automatically selected by the utilization of the depth information of the image, the seed regions of the target and the seed regions of the background do not need to be marked manually and alternately, region characteristics of the depth image are directly used for determining the seed regions instead of edge characteristics, and therefore high robustness is achieved.