Bayesian damage recognition in document images based on a joint global and local homogeneity model

Tan Lu, Ann Dooms

Abstract: Highlights•A global homogeneity measure is developed by characterizing connected pixels using a probabilistic graph model.•A local homogeneity measure is developed by modeling neighborhood transition around an individual pixel based on propagation of wavelet approximation coefficients.•Global and local homogeneity measures are jointly modeled using a Bayesian framework with a Markov random field (MRF) prior.•Probabilistic recognition of damages in document images based on the joint global and local homogeneity model and Markov chain Monte Carlo (MCMC) sampling.