Aimed at resolving the problems of sensitivity to noise and over-segmentation existing in traditional watershed algorithm,a new image segmentation method-CWAC is presented. First,an image is separated into a large number of small partitions by watershed algorithm and the characteristic parameters are calculated. Second,CWAC method merges different regions of homogeneity with ant colony clustering algorithm to gain result of image segmentation. CAWC algorithm can successfully solve the over-segmentation problem and at the same time it can reduce the computational times of ant colony clustering. In order to be more accurate and efficient at clustering ant colony,a new visibility based on intensity distribution and spatial information is defined. Experimental results show that CWAC can segment objective quickly and accurately and it is a practicable method for the image segmentation .