A Neuro-Heuristic Approach for Segmenting Handwritten Arabic Text

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dc.contributor.author Haraty, Ramzi
dc.contributor.author Hamid, Alaa
dc.date.accessioned 2018-03-01T11:25:23Z
dc.date.available 2018-03-01T11:25:23Z
dc.date.copyright 2001 en_US
dc.date.issued 2018-03-01
dc.identifier.isbn 0769511651 en_US
dc.identifier.uri http://hdl.handle.net/10725/7168
dc.description.abstract The segmentation and recognition of Arabic handwritten text has been an area of great interest in the past few years. However, only a small number of research papers and reports have been published in this area, due to the difficult problems associated with Arabic handwritten text processing. In this work, a technique is presented that segments 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. Two major problems were encountered. First, although the segmentation phase proved to be successful in the vertical segmentation of connected blocks of characters, it couldn't segment characters that were overlapping horizontally. Second, segmentation of handwritten Arabic text depends largely on contextual information, and not just on topographic features extracted from the characters. en_US
dc.description.sponsorship Arab Computer Society en_US
dc.description.sponsorship IEEE Computer Society Technical Council on Software Engineering en_US
dc.description.sponsorship IEEE Computer Society Technical Committee on Computer Architecture en_US
dc.language.iso en en_US
dc.publisher IEEE Computer Society en_US
dc.subject Computer systems -- Congresses en_US
dc.subject Application software -- Congresses en_US
dc.subject Technology transfer -- Congresses en_US
dc.title A Neuro-Heuristic Approach for Segmenting Handwritten Arabic Text en_US
dc.type Conference Paper / Proceeding 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.description.physdesc xix, 565 pages : illustrations en_US
dc.publication.place Los Alamitos, Calif. en_US
dc.keywords Text recognition en_US
dc.keywords Handwriting recognition en_US
dc.keywords Feature extraction en_US
dc.keywords Artificial Neural Networks en_US
dc.keywords Pixel en_US
dc.keywords Text processing en_US
dc.keywords Neural networks en_US
dc.keywords Data mining en_US
dc.keywords Shape en_US
dc.keywords Indexes en_US
dc.description.bibliographiccitations Includes bibliographical references. en_US
dc.identifier.ctation Hamid, A., & Haraty, R. (2001). A neuro-heuristic approach for segmenting handwritten Arabic text. In Computer Systems and Applications, ACS/IEEE International Conference on. 2001 (pp. 110-113). IEEE. en_US
dc.author.email rharaty@lau.edu.lb en_US
dc.conference.date 25-29 June 2001 en_US
dc.conference.pages 110-113 en_US
dc.conference.place Beirut, Lebanon en_US
dc.conference.title ACS/IEEE International Conference on Computer Systems and Applications en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url http://ieeexplore.ieee.org/abstract/document/933960/ en_US
dc.orcid.id https://orcid.org/0000-0002-6978-3627 en_US
dc.publication.date 2001 en_US
dc.author.affiliation Lebanese American University en_US

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