Deep Recognition-based Character Segmentation in Handwritten Syriac Manuscripts

Deep Recognition-based Character Segmentation in Handwritten Syriac ManuscriptsSyriaca.org: The Syriac Reference PortalThe National Endowment for the HumanitiesThe International Balzan Prize FoundationDavid A. Michelsoncbsc_adminRecord added to Zotero bycbsc_adminSyriaca.org: The Syriac Reference Portalhttp://syriaca.org/cbss/NJY4JSZU/tei

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2024-08-15-04:00

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CREATED: This bibl record was autogenerated from a Zotero record.RitaFermanianCharlesYaacoubAdibAklPetraBilaneDeep Recognition-based Character Segmentation in Handwritten Syriac Manuscriptshttp://syriaca.org/cbss/NJY4JSZUhttps://www.zotero.org/groups/a_comprehensive_bibliography_on_syriac_studies/items/NJY4JSZUhttps://www.zotero.org/groups/4861694/items/NJY4JSZU2020 Tenth International Conference on Image Processing: Theory, Tools and Applications (IPTA), 2020-11-09, 2020-11-12 Paris, FranceParisInstitute of Electrical and Electronics Engineers20201-6Ancient Syriac manuscripts represent a valuable cultural heritage for a large community, mainly in the region of the Middle East. Digitization of these manuscripts plays a major role in preserving this heritage and making it publicly available without the need to access the original paper versions. In this context, this paper presents a recognition-based algorithm for character segmentation in handwritten Syriac manuscripts. A convolutional neural network is used as a classifier for character recognition in a variable-size sliding window that spans individual word images. The classifier also provides likelihood values that are then used to determine suitable segmentation points for individual characters. Since the classifier is a core component of the segmentation algorithm, the proposed approach allows for joint character segmentation and recognition, thus providing a means for automated document indexing and content-based search and retrieval. Fermanian, Rita, Charles Yaacoub, Adib Akl, and Petra Bilane. “Deep Recognition-Based Character Segmentation in Handwritten Syriac Manuscripts.” In 2020 Tenth International Conference on Image Processing: Theory, Tools and Applications (IPTA), 2020-11-09, 2020-11-12 Paris, France, 1–6. Paris: Institute of Electrical and Electronics Engineers, 2020. Rita Fermanian et al., Deep Recognition-Based Character Segmentation in Handwritten Syriac Manuscripts, in 2020 Tenth International Conference on Image Processing: Theory, Tools and Applications (IPTA), 2020-11-09, 2020-11-12 Paris, France (Paris: Institute of Electrical and Electronics Engineers, 2020), 1–6.XIX-XXI CEXXI CEdigitalmanuscriptspaleography