An MLP for Binarizing Images of Old Manuscripts

Ancient Arabic manuscripts' processing and analysis are very difficult tasks and are likely to remain open problems for many years to come. In this paper we tackle the problem of foreground/background separation in old documents. Our approach uses a back-propagation neural network to directly classify image pixels according to their neighborhood. We tried several multilayer Perceptron topologies and found experimentally the optimal one. Experiments were run on synthetic data obtained by image fusion techniques. The results are very promising compared to state-of-the-art techniques.