In this paper, a novel method for the unsupervised segmentation of textured images is presented. Textures are modeled as spatial interactions between pixels. Thus, a certain window size is required to extract texture features and to estimate texture boundaries by using the features. As long as the size of the window is fixed over the whole of an image, we cannot accurately estimate texture regions that have similar properties. In this paper the problem of selection of an appropriate size for window used to estimate homogeneous texture regions is investigated via hypothesis and testing. Experiments on segmentation of textures in synthetic and natural images show the effectiveness of the method.