Off-line handwriting recognition system based on GA and visual encoding

Authors:
Monji Kherallah;Haikal El Abed;Fatma Bouri;Abdelkarim El Baati;Adel M. Alimi
Affiliations:
Research Group on Intelligent Machines (REGIM), (ENIS), Sfax, Tunisia;Technische Universität, Braunschweig, Germany;Research Group on Intelligent Machines (REGIM), (ENIS), Sfax, Tunisia;Research Group on Intelligent Machines (REGIM), (ENIS), Sfax, Tunisia;Research Group on Intelligent Machines (REGIM), (ENIS), Sfax, Tunisia
Venue:
Proceedings of the International Workshop on Multilingual OCR
Year:
2009

Citing 5
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On-line Arabic handwriting recognition system based on visual encoding and genetic algorithm

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Abstract

Our day, the communication technology has been progressed. The handwriting is one of the most familiar communication media. Both online and off line recognition of the handwriting are largely presented in literature. In this paper, we proceed to reconstruct the temporally order from the scanned handwritten Arabic words. We used the GA system to recognize the handwritten words. The input signal presents a string of visual codes. Note that the last one can be either directly collected from a PDA or it can be the restored signal from an image of handwritten script. To validate our approach we used the IfN/ENIT dataset.