Evidential Combination of Multiple HMM Classifiers for Multi-script Handwritting Recognition

In this work, we focus on an improvement of a multi-script 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.

• Type: Conference
• Year: 2010
• Where: IPMU
• Authors: Yousri Kessentini, Thomas Burger, Thierry Paquet
• Keywords: HMM Based Classifiers, HMM Classifiers, Information Management, IPMU 2010, Multi-script Handwritting Recognition