Segmenting Handwritten Arabic Text

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dc.contributor.author Haraty, Ramzi A.
dc.contributor.author Hamid, Alaa
dc.date.accessioned 2018-03-22T13:39:48Z
dc.date.available 2018-03-22T13:39:48Z
dc.date.copyright 2002 en_US
dc.identifier.issn 0091-7036 en_US
dc.identifier.uri http://hdl.handle.net/10725/7256
dc.description.abstract The segmentation and recognition of Arabic handwritten text has been an area of great interest in the past few years. However, a small number of research papers and reports have been published in this area. There are several major problems with Arabic handwritten text processing: Arabic is written cursively and many external objects are used such as dots, ‘Hamza’, ‘Madda’, and diacritic objects. In addition, Arabic characters have more than one shape according to their position inside a word. More than one character can also share the same horizontal space, creating vertically overlapping connected or disconnected blocks of characters. This makes the problem of segmentation of Arabic text into characters, and their classification even more difficult. In this work a technique is presented that segments difficult handwritten Arabic text. A conventional algorithm is used for the initial segmentation of the text into connected blocks of characters. The algorithm then generates pre-segmentation points for these blocks. A neural network is subsequently used to verify the accuracy of these segmentation points. Another conventional algorithm uses the verified segmentation points and segments the connected blocks of characters. en_US
dc.language.iso en en_US
dc.title Segmenting Handwritten Arabic Text 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 International Journal of Computer and Information Science en_US
dc.journal.volume 3 en_US
dc.journal.issue 4 en_US
dc.keywords Artificial Neural Networks en_US
dc.keywords Optical character recognition en_US
dc.identifier.ctation Haraty, R. A., & Hamid, A. (2002). Segmenting Handwritten Arabic Text. ACIS International Journal of Computer and Information Science (IJCIS), 3 (4). 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://www.acisinternational.org/journal/Volume3-4.htm en_US
dc.orcid.id https://orcid.org/0000-0002-6978-3627 en_US
dc.author.affiliation Lebanese American University en_US

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