• DocumentCode
    3109219
  • Title

    The GVF Snake with a Minimal Path Approach

  • Author

    Sun, Chensheng ; Lam, Kin-Man

  • Author_Institution
    Hong Kong Polytech. Univ., Hong Kong
  • fYear
    2007
  • fDate
    11-13 July 2007
  • Firstpage
    223
  • Lastpage
    228
  • Abstract
    In this paper we propose a contour extraction method based on the active contour model, which uses the GVF snake to obtain the initial segments for a contour; and then a minimal path method for the refinement stage, to obtain an accurate and more robust result. By employing the minimal path method to find missing segments between pairs of nodes defined on the contour obtained by the GVF snake, our algorithm is able to detect deep concave parts of object boundary, and works well even when the snake initialization is not very good.
  • Keywords
    edge detection; feature extraction; image segmentation; object detection; GVF snake method; contour extraction; edge detection; image segmentation; minimal path method; object boundary detection; Active contours; Data mining; Deformable models; Digital images; Image edge detection; Object detection; Robustness; Signal processing; Signal processing algorithms; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference on
  • Conference_Location
    Melbourne, Qld.
  • Print_ISBN
    0-7695-2841-4
  • Type

    conf

  • DOI
    10.1109/ICIS.2007.178
  • Filename
    4276385