Offline Handwritten Arabic Word Recognition Using HMM - a Character Based Approach without Explicit Segmentation

Volker Märgner (1) , Haikal El Abed (1) , Mario Pechwitz (1)

1 IFN - Institut for Communications Technology

This paper presents the IfN's Offline Handwritten Arabic Word Recognition System. The system uses Hidden Markov Models (HMM) for word recognition, and is based on character recognition without explicit segmentation. The first part of this paper deals with databases for word recognition systems, and in particular, the IFN/ENIT -database. The second part gives a short description of the pre-processing, normalisation, and feature extraction methods needed for this system. The final part gives a practical approach to the HMM-Recogniser used in our system and some results are presented.

Domaines: Traitement du signal et de l'image [eess.SP]; Automatique / Robotique; Traitement du signal et de l'image [eess.SP]

Volker Märgner, Haikal El Abed, Mario Pechwitz. Offline Handwritten Arabic Word Recognition Using HMM - a Character Based Approach without Explicit Segmentation. Sep 2006, pp.259-264. ⟨hal-00112048⟩