• DocumentCode
    250520
  • Title

    A geometric approach to stroke extraction for the Chinese calligraphy robot

  • Author

    Yuandong Sun ; Huihuan Qian ; Yangsheng Xu

  • Author_Institution
    Dept. of Mech. & Autom. Eng., Chinese Univ. of Hong Kong, Hong Kong, China
  • fYear
    2014
  • fDate
    May 31 2014-June 7 2014
  • Firstpage
    3207
  • Lastpage
    3212
  • Abstract
    Known as “the art of strokes”, Chinese calligraphy expresses its aesthetic through the strokes. A calligraphy learner practise the strokes and compose a calligraphic character by the strokes thereafter. Following the same process, the calligraphy robot, Callibot [2] needs to extract the strokes from a character. Therefore, we propose an approach to extract strokes using the geometric properties on the contour(s) of a character. A key discovery is that if two strokes intersect, the contour is concave; otherwise it is convex. The curvature vector defined in [1] is used to locate the vertexes whose interior angles are greater than 180° (these vertexes are named as C-points). C-points separate the contours into sub-contours. The corresponding sub-contours then form the basic strokes (i.e. dot stroke, horizontal stroke, vertical stroke, left-falling stroke and right-falling stroke). The experimental results show that this approach is feasible of extracting strokes from characters. This research is also useful for Chinese character recognition and calligraphic styles classification.
  • Keywords
    art; feature extraction; human-robot interaction; robot vision; C-points; Callibot; Chinese calligraphy robot; Chinese character recognition; calligraphic character; calligraphic styles classification; calligraphy learner; curvature vector; geometric properties; geometric stroke extraction approach; stroke art; subcontours; Art; Character recognition; Joining processes; Robots; Testing; Vectors; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2014 IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Type

    conf

  • DOI
    10.1109/ICRA.2014.6907320
  • Filename
    6907320