Stochastic model for boundary detection

摘要

A Markov model is presented for the joint distribution of grey levels and boundary labels in digital images, and perceived as embodying prior expectations about boundary behaviour. The detected boundaries correspond to a local maximum in the conditional distribution over all possible boundary interpretations given the observed intensity image; this is obtained by a highly parallel Monte Carlo algorithm called ‘stochastic relaxation’.