Abstract: An approach is proposed based on the combined color information and texture information for color-texture image segmentation. The compacted multi-scale texture information is extracted by using singular value decomposition and principal component analysis dimension reduction under decomposing the multi-scale structure tensor, and then it is integrated with scale information and color information for improving the description ability to color-texture. To avoid the phenomenon such as over-segmentation and error segmentation appeared, the regional credible fusion degree is computed by combining four kinds of region information, such as region adjacency relationship, region size, common edge between regions, and J-divergence distance. Meanwhile, through the reasonable judgment we can merge and delete some regions which own the lower regional credible fusion degree. Then, a substantial of experiment analysis and comparison are carried out on some synthesis color-texture images and real natural scene images, which demonstrate the superiority of our proposed method, such as the high segmentation accuracy, outperforming visual entirety and closing to ground truth.

Key words: regional credible fusion, color-texture, image segmentation, multilayer graph cut model