• DocumentCode
    327722
  • Title

    A deformable model-based image segmentation algorithm for shapes with corners

  • Author

    Zhang, Zixin ; Braun, Michael

  • Author_Institution
    Dept. of Appl. Phys., Univ. of Technol., Sydney, NSW, Australia
  • Volume
    1
  • fYear
    1998
  • fDate
    16-20 Aug 1998
  • Firstpage
    392
  • Abstract
    Deformable models are generally applied to simple images with smooth region boundaries. Segmentation of objects with high curvature shapes (corners) is limited by the models´ finite node density and their intrinsic smoothness constraint. Previous solutions to segmentation of objects with corners are based on relating the smoothness constraint at the candidate corner nodes. While allowing a contour to bend at those nodes, these solutions do not provide a force to propel nodes into corners. In this paper, we propose a deformable model algorithm for segmenting objects containing high curvature shapes with subresolution accuracy, which provides a driving force for nodes to slide into corners along object boundaries. The algorithm can be applied to both 2D and 3D deformable models
  • Keywords
    edge detection; image segmentation; mesh generation; stereo image processing; 2D deformable model; 3D deformable models; corner nodes; curvature shapes; image segmentation; object contour; triangular mesh; Active contours; Convergence; Deformable models; Energy measurement; Force measurement; Image segmentation; Physics; Scalability; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
  • Conference_Location
    Brisbane, Qld.
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-8512-3
  • Type

    conf

  • DOI
    10.1109/ICPR.1998.711163
  • Filename
    711163