Arabic text recognition

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dc.contributor.author Haraty, Ramzi
dc.date.accessioned 2017-01-31T09:02:21Z
dc.date.available 2017-01-31T09:02:21Z
dc.date.copyright 2004 en_US
dc.date.issued 2017-01-31
dc.identifier.issn 1683-3198 en_US
dc.identifier.uri http://hdl.handle.net/10725/5113
dc.description.abstract The issue of handwritten character recognition is still a big challenge to the scientific community. Several approaches to address this challenge have been attempted in the last years, mostly focusing on the English pre-printed or handwritten characters space. Thus, the need to attempt a research related to Arabic handwritten text recognition. Algorithms based on neural networks have proved to give better results than conventional methods when applied to problems where the decision rules of the classification problem are not clearly defined. Two neural networks were built to classify already segmented characters of handwritten Arabic text. The two neural networks correctly recognized 73% of the characters. However, one hurdle was encountered in the above scenario, which can be summarized as follows: there are a lot of handwritten characters that can be segmented and classified into two or more different classes depending on whether they are looked at separately, or in a word, or even in a sentence. In other words, character classification, especially handwritten Arabic characters, depends largely on contextual information, not only on topographic features extracted from these characters. en_US
dc.language.iso en en_US
dc.title Arabic text recognition en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 199729410 en_US
dc.author.department Computer Science and Mathematics en_US
dc.description.embargo N/A en_US
dc.relation.journal The International Arab Journal of Information Technology en_US
dc.journal.volume 1 en_US
dc.journal.issue 2 en_US
dc.article.pages 156-163 en_US
dc.keywords Arabic text classification en_US
dc.keywords Artificial neural networks en_US
dc.identifier.ctation Haraty, R. A., & Ghaddar, C. (2004). Arabic text recognition. Int. Arab J. Inf. Technol., 1(2), 156-163. en_US
dc.author.email rharaty@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url http://s3.amazonaws.com/academia.edu.documents/39259926/02-Ramzi.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1485853939&Signature=CuWNQKhbwYUX2QNIOKrOEhQ7vBs%3D&response-content-disposition=inline%3B%20filename%3DArabic_Text_Recognition.pdf en_US
dc.orcid.id https://orcid.org/0000-0002-6978-3627
dc.author.affiliation Lebanese American University en_US

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