Segmentation of random textures by morphological and linear operators

We propose a linear and a morphological approach for the characterization and segmentation of binary and digital random textures. We focus on descriptors at the level of pixels in images, combined with statistical learning to select and weight them. The approach is illustrated on simulations of textures patchworks, for which errors of classification can be evaluated.