On retrieving textured images from an image database

We discuss the problem of an image-based query for retrieving images represent ed by sufficiently large regions of uniform textures from image data bases. A distance measure to match the query image to the database content under possible orientation and scale differences between the textures of the same type is proposed. The measure is based on comparing the gray-level difference histograms collected in accord with the structure of multiple pairwise pixel interactions in the subimages to be matched. The interaction structure is recovered with a proposed learning scheme for a Markov random field image model with Gibbs probability distribution. Texture rotation and scaling are handled to some extent by similar transformations of the interaction structures. Several results on experimental databases containing digitized textured images are presented. Copyright (C) 1996 Pattern Recognition Society. Published by Elsevier Science Ltd.