<FONT face=Verdana>A nonparametric Wasserstein distance-based active contour model that is able to utilize image histogram information in local region is presented. To quantify the similarity between two regions

we proposed to compare their respective histograms using the Wasserstein distance; Due to a Gaussian kernel introduced

intensity information in local regions is extracted and embedded in model to guide the motion to overcome the difficulties in image segmentation caused by intensity inhomogeneities. In addition

the regularity of the level set function is intrinsically preserved by the level set regularization term to ensure accurate computation and avoids expensive reinitialization of the evolving level set function. Experiment results prove that our model segments texture images with intensity inhomogeneity effectively.