Towards an educational tool for Arabic handwriting learning

In today many students produce a wrong and illegible handwriting. The traditional approach for handwriting teaching needs a long hour of handwriting practice, and teacher needs a lot of time to check the handwriting errors. Unfortunately, this is not feasible in many cases. In this paper, we introduce an automated educational tool for Arabic Handwriting detection errors, such as the stroke production errors, stroke sequence errors, stroke relationship errors and stroke interline errors, to help students to generate clear handwriting. Firstly, we used an attributed relational graph to locate the handwriting errors. Secondly, an immediate feedback is provided to the students to correct them.