Multi Resolution Layout Analysis of Medieval Manuscripts Using Dynamic MLP

This paper describes a generic layout analysis system for historical documents. It presents the architecture of a pyramidal approach using three analysis levels. Each level consists of a classifier using machine learning techniques where the output of the upper level is used as a feature in the lower level. The current implementation uses a so called Dynamic Multi-Layer perceptron (DMLP), which is a natural extension of MLP classifiers. The system is evaluated on medieval documents for which a multi-layer model is used to discriminate among 10 classes organized hierarchically.