Multi-agent Systems for Arabic Handwriting Recognition
DOI:
https://doi.org/10.9781/ijimai.2017.03.012Keywords:
Image Processing, Segmentation, Artificial Intelligence, Multi-Agent Systems, Recognition, Feature Extraction, Arabic Documents, Handwritten Character RecognitionAbstract
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 Kénitra in a publicly open presentation. After the presentation, Boulid was awarded with the highest grade (Très honorable avec félicitations de jury).Downloads
References
Boulid, Y. Arabic handwritten recognition in an offline mode. PhD thesis, Faculty of Science Kénitra, University Ibn Tofail, December 2016.
Boulid, Y., & Elkettani, M. Y. (2014). Approach for Arabic Handwritten Image Processing: Case of Text Detection in Degraded Documents. International Journal of Computer Applications, Vol. 101, N° 14, Pages 35-42.
Boulid, Y., Souhar, A., & Elkettani, M. Y. (2016). Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes. International Journal of Interactive Multimedia and Artificial Intelligence, (Special Issue on Artificial Intelligence Underpinning), Vol. 4, Nº1 Pages 31-36.
Boulid, Y., Souhar, A., & Elkettani, M. Y. (2016). Segmentation approach of Arabic manuscripts text lines based on multi agent systems. International Journal of Computer Information Systems and Industrial Management Applications, Vol. 8, Pages 173 - 183.
Boulid, Y., Souhar, A., & Elkettani, M. Y. (2017). Handwritten Character Recognition Based on the Specificity and the Singularity of the Arabic Language. International Journal of Interactive Multimedia and Artificial Intelligence, (Regular Issue), Vol. 4, Nº4 Pages 45-53.
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