Journal of Information Processing Systems

  • 제10권4호
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  • Pages.503-522
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  • 2014
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Graphemes Segmentation for Arabic Online Handwriting Modeling

  • Boubaker, Houcine (Research Groups in Intelligent Machines (REGIM), National School of Engineers ENIS, University of Sfax) ;
  • Tagougui, Najiba (Research Groups in Intelligent Machines (REGIM), National School of Engineers ENIS, University of Sfax) ;
  • El Abed, Haikal (Institute for Communications Technology (IfN), Technische Universitat) ;
  • Kherallah, Monji (Research Groups in Intelligent Machines (REGIM), National School of Engineers ENIS, University of Sfax) ;
  • Alimi, Adel M. (Research Groups in Intelligent Machines (REGIM), National School of Engineers ENIS, University of Sfax)
  • 투고 : 2013.07.31
  • 심사 : 2013.11.17
  • 발행 : 2014.12.31
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초록

In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

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피인용 문헌

  1. Arabic Online Handwriting Recognition (AOHR) vol.50, pp.3, 2017, https://doi.org/10.1145/3060620