Evidential combination of multiple HMM classifiers for multi-script handwriting recognition

Authors:
Yousri Kessentini;Thomas Burger;Thierry Paquet
Affiliations:
Université de Rouen, Laboratoire LITIS, St Etienne du Rouvray, France;Université Européenne de Bretagne, Université de Bretagne-Sud, CNRS, Vannes cedex, France;Université de Rouen, Laboratoire LITIS, St Etienne du Rouvray, France
Venue:
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Year:
2010

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Abstract

In this work, we focus on an improvement of a multiscript handwritting recognition system using a HMM based classifiers combination. The improvement relies on the use of Dempster-Shafer theory to combine in a finer way the probabilistic outputs of the HMM classifiers. The experiments are conducted on two public databases written on two different scripts : IFN/ENIT (latin script) and RIMES (arabic script). The obtained results are compared with the classical algorithms of the field and the superiority of the proposed approach is shown.