01358nas a2200157   4500008004100000245008500041210006900126260001800195300001400213520078800227100001701015700002101032700002101053700000501074856012101079       2003                        eng d00aUnsupervised segmentation of color textured images using a multi-layer MRF model0 aUnsupervised segmentation of color textured images using a multi  bIEEEc2003///  a961 - 9643 a<p>Herein, we propose a novel multi-layer Markov random field (MRF) image segmentation model which aims at combining color and texture features: Each feature is associated to a so called feature layer, where an MRF model is defined using only the corresponding feature. A special layer is assigned to the combined MRF model. This layer interacts with each feature layer and provides the segmentation based on the combination of different features. The model is quite generic and isn't restricted to a particular texture feature. Herein we will test the algorithm using Gabor and MRSAR texture features. Furthermore, the algorithm automatically estimates the number of classes at each layer (there can be different classes at different layers) and the associated model parameters.</p>1 aKato, Zoltan1 aPong, Ting Chuen1 aQiang, Song, Guo1 a  uhttps://inf.u-szeged.hu/publication/unsupervised-segmentation-of-color-textured-images-using-a-multi-layer-mrf-model