Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/602
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dc.contributor.authorHajj Mohamad, Ramy Alen_US
dc.contributor.authorMokbel, Chaficen_US
dc.date.accessioned2020-12-23T08:33:18Z-
dc.date.available2020-12-23T08:33:18Z-
dc.date.issued2016-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/602-
dc.description.abstractFor document analysis and recognition systems, script identification is considered as an important preprocessing step in the design of multi-scripts OCR system. In this paper, we propose a novel HMM based identification system to recognize on only one level the writing type (handwritten or machine-printed) and the script nature (Arabic or Latin) of the input image. The proposed system is based on Histogram of Oriented Gradient (HOG) features which have demonstrated an interesting properties for script characterization. Experiments have been conducted on word and line images collected from public databases and show promising results.en_US
dc.language.isoengen_US
dc.titleHMM-based arabic handwritten cursive recognition systemen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Hybrid Intelligent Systems (16th : 2016 : Morocco)en_US
dc.contributor.affiliationDepartment of Electrical Engineeringen_US
dc.description.startpage298en_US
dc.description.endpage307en_US
dc.date.catalogued2019-05-29-
dc.description.statusPublisheden_US
dc.identifier.OlibID192156-
dc.relation.ispartoftextProceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016)en_US
dc.provenance.recordsourceOliben_US
Appears in Collections:Department of Electrical Engineering
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