Probabilistic hierarchical morphological segmentation of textures

Abstract

A general methodology is introduced for texture segmentation in binary, scalar, or multispectral images. Textural information is obtained from morphological operations of images. Starting from a fine partition of the image in regions, hierarchical segmentations are designed in a probabilistic framework by means of probabilistic distances conveying the textural information, and of random markers accounting for the morphological content of the regions and of their spatial arrangement.