• DocumentCode
    1244937
  • Title

    Efficient morphological shape representation

  • Author

    Reinhardt, Joseph M. ; Higgins, William E.

  • Author_Institution
    Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA
  • Volume
    5
  • Issue
    1
  • fYear
    1996
  • fDate
    1/1/1996 12:00:00 AM
  • Firstpage
    89
  • Lastpage
    101
  • Abstract
    Mathematical morphology is well suited to capturing geometric information. Hence, morphology-based approaches have been popular for object shape representation. The two primary morphology-based approaches-the morphological skeleton and the morphological shape decomposition (MSD)-each represent an object as a collection of disjoint sets. A practical shape representation scheme, though, should give a representation that is computationally efficient to use. Unfortunately, little work has been done for the morphological skeleton and the MSD to address efficiency. We propose a flexible search-based shape representation scheme that typically gives more efficient representations than the morphological skeleton and MSD. Our method decomposes an object into a number of simple components based on homothetics of a set of structuring elements. To form the representation, the components are combined using set union and set difference operations. We use three constituent component types and a thorough cost-based search strategy to find efficient representations. We also consider allowing object representation error, which may yield even more efficient representations
  • Keywords
    computational geometry; image representation; mathematical morphology; search problems; set theory; cost-based search strategy; disjoint sets; efficiency; flexible search-based shape representation; geometric information; homothetics; image representation; mathematical morphology; morphological shape decomposition; morphological shape representation; morphological skeleton; object representation error; object shape representation; set difference operations; set union; structuring elements; Cancer; Digital images; Humans; Image analysis; Image coding; Image reconstruction; Morphology; Pattern recognition; Shape; Skeleton;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.481673
  • Filename
    481673