• DocumentCode
    594809
  • Title

    Accurate junction detection and reconstruction in line-drawing images

  • Author

    The-Anh Pham ; Delalandre, Mathieu ; Barrat, Sabine ; Ramel, Jean-Yves

  • Author_Institution
    Lab. of Comput. Sci. (LI), Francois Rabelais Univ., Tours, France
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    693
  • Lastpage
    696
  • Abstract
    In this paper, we present an approach for junction detection and reconstruction in line-drawing images. Our approach is shifted to a problem of high curvature point detection from the skeleton of image. Like this, it is independent of any vectorization process and parameter free. The junction reconstruction stage takes benefit of the reliable skeleton segments and their topological relations to reconstruct junctions and make their positions accurate. The experimental results show that the proposed method is competitive with other baseline methods and can achieve accurate junction detection with some pixel errors.
  • Keywords
    image reconstruction; object detection; accurate junction detection; high curvature point detection; junction reconstruction; line-drawing images; pixel errors; skeleton segments; vectorization process; Detectors; Image reconstruction; Image segmentation; Junctions; Noise; Reliability; Skeleton;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460229