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

One of the most promising methods of interacting with small portable computing devices, such as personal digital assistants, is the use of handwriting. In order to make this communication method more natural, we propose to observe visually the writing process on an ordinary paper and to automatically recover the pen trajectory from numerical tablet sequences. On the basis of this work, we developed a handwriting recognition system based on visual coding and genetic algorithm ''GA''. The system is applied on Arabic script. In this paper, we will present the different steps of the handwriting recognition system. We focus our contribution on the encoding system and the fitness function conception used as basic steps of the GA. A new approach based on visual indices similarity is developed to calculate the evaluation function. We optimize the times cooling of our system to give the final output (proposed words). Several experimentations are developed using an Arabic data set words extracted from ''LMCA'' database elaborated in our laboratory by 24 participants. The results obtained are very promising and prove that our new method based on hybridization between visual codes and GA is a powerful method.

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