HMM Based Approach for Handwritten Arabic Word Recognition Using theIfn Enit IFN/ENIT-Database

An offline recognition system for Arabic handwritten words is presented. The recognition system is based on a semi-continuous 1-dimensional HMM. From each binary word image normalization parameters were estimated. First height, length, and baseline skew are normalized, then features are collected using a sliding window approach. This paper presents these methods in more detail. Some parameters were modified and the consequent effect on the recognition results are discussed. Significant tests were performed using the new IFN/ENIT - database of handwritten Arabic words. The comprehensive database consists of 26459 Arabic words (Tunisian town/village names) handwritten by 411 different writers and is free for non-commercial research. In the performed tests we achieved maximal recognition rates of about 89% on a word level

IFN/ENIT - database of handwritten Arabic words

ABSTRACT. In this paper we are presenting a new database with handwritten Arabic town/village names. For each name the ground truth information, e.g. the sequence of character shapes, some style information, and the baseline are coded. 411 writers filled forms with about 26400 names containing more than 210000 characters. The database is described in detail. It is designed for training and testing recognition systems for handwritten Arabic words. The IFN/ENIT-database is available for the purpose of research. RÉSUMÉ: Dans cet article on présente une novelle base de données, qui contient des noms manuscrits de villes/villages arabes. Pour chaque nom les informations de base, par exemple l'ordre des formes de caractère, les informations sur le style de l'écriture, et la ligne de base sont codées. 411 auteurs ont rempli des formulaires avec plus de 26400 noms contenant plus de 210 000 caractères. La base de données est décrite en détail, et elle est conçue pour la formation et l'essai des systèmes d'identification pour les mots arabes manuscrits. La base de données-IFN/ENIT est disponible pour la recherche