• DocumentCode
    318234
  • Title

    On topological deep-structure segmentation

  • Author

    Kalitzin, Stiliyan N. ; Romeny, Bart Ter Haar ; Viergever, Max

  • Author_Institution
    Image Sci. Inst., Utrecht Univ., Netherlands
  • Volume
    2
  • fYear
    1997
  • fDate
    26-29 Oct 1997
  • Firstpage
    863
  • Abstract
    A hierarchical segmentation model is obtained by using linear scale evolution of gray-scale images. At each scale segments are generated as Voronoi diagrams with a distance measure defined on the image landscape. The set of centers of the Voronoi cells is the set of local extrema of the gray-scale image. This set is localized by using the winding number distribution of the gradient vector field. Scale evolution induces hierarchical structure of embedded segments. Objects defined at coarser scales “decompose” into sub-objects at finer scales. The process is naturally described in terms of singularity catastrophes within the smooth scale evolution. Alternatively, we present a purely topological segmentation procedure, based on singular isophotes. The last are generated by the set of saddle points in the image which are detected also with the topological winding-number method
  • Keywords
    catastrophe theory; computational geometry; image segmentation; topology; Voronoi cells; Voronoi diagrams; distance measure; gradient vector field; gray-scale images; hierarchical segmentation model; image segmentation; linear scale evolution; saddle points; singular isophotes; singularity catastrophes; topological deep-structure segmentation; winding number distribution; Diffusion processes; Euclidean distance; Gray-scale; Image segmentation; Joining processes; Kernel; Level measurement; Pattern analysis; Tensile stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1997. Proceedings., International Conference on
  • Conference_Location
    Santa Barbara, CA
  • Print_ISBN
    0-8186-8183-7
  • Type

    conf

  • DOI
    10.1109/ICIP.1997.638633
  • Filename
    638633