Document Image Binarisation Using Markov Field Model

Abstract

This paper presents a new approach for the binarization of seriously degraded manuscript. We introduce a new technique based on a Markov Random Field (MRF) model of the document. Depending on the available information, the model parameters (clique potentials) are learned from training data or computed using heuristics. The observation model is estimated thanks to an expectation maximization (EM) algorithm which extracts text and paper’s features. The performance of the proposition is evaluated on several types of degraded document images where considerable background noise or variation in contrast and illumination exist.