Markov random field based image labeling with parameter estimation by error backpropagation

The authors investigate a method of efficiently labeling images using the Markov random field (MRF). The MRF model is defined on the region adjacency graph and the labeling is then optimally determined using simulated annealing. The MRF model parameters are automatically estimated using an error backpropagation network. The proposed method is analyzed through experiments using real natural scene images.