Abstract
This paper aims to give a presentation of the PhD defended by Boulid Youssef on December 26th, 2016 at University Ibn Tofail, entitled “Arabic handwritten recognition in an offline mode”. The adopted approach is realized under the multi agent paradigm. The dissertation was held in Faculty of Science Kenitra in a publicly open presentation. After the presentation, Boulid was awarded with the highest grade (Tres honorable avec felicitations de jury).
Highlights
This paper aims to give a presentation of the PhD defended by Boulid Youssef on December 26th, 2016 at University Ibn Tofail, entitled “Arabic handwritten recognition in an offline mode”
On December 26th, 2016, Boulid Youssef defended his PhD thesis related with Arabic handwritten recognition [1]
Based on the fact that Arabic is written from right to left, we have found that extracting features from the right portion rather than from the whole character’s image allows enhancing the recognition rate
Summary
On December 26th, 2016, Boulid Youssef defended his PhD thesis related with Arabic handwritten recognition [1]. From this point of view we are interested in analyzing the problems of the recognition of handwritten document by taking inspiration from the mechanisms of what we think the human reader uses during the reading process This problem is modeled under the multi-agent systems paradigm while taking into consideration the specific characteristics of the Arabic language. In this context, the contribution of the thesis concerns the recognition of handwritten Arabic documents and precisely the pre-processing, the line segmentation and the character recognition stages [1]. To overcome the problem that resides in the traditional approaches, which is the use of the phases in the recognition process in a sequential manner, we have proposed an agent-based modeling offering the possibility to implement different strategies of human reading. We believe that such a platform should be based on multi-agent systems offering the possibility of implementing and integrating the different recognition stages in parallel
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