A simple unsupervised MRF model based image segmentation approach

A simple technique has been suggested to obtain optimal segmentation based on tonal and textural characteristics of an image using Markov random field (MRF) model. The technique takes an initially over segmented image as well as the original image as its inputs and defines an MRF over the region adjacency graph (RAG) of the initially segmented regions. A tonal-region based segmentation technique due to Kartikeyan and Sarkar [23] has been used for initial segmentation. The energy function has been defined over the first order cliques of the MRF. The essence of this approach is primarily based on quantitative values of the second order statistics on region characteristics and consequently deciding upon action of merging neighboring regions using F-statistic. The effectiveness of our approach is demonstrated with wide variety real life examples viz., indoor, outdoor and satellite and a comparison of its output with that of a recent work in the literature has been provided.