• DocumentCode
    1116634
  • Title

    Global Shape Analysis by k-Syntactic Similarity

  • Author

    Bjorklund, Carolyn M. ; Pavlidis, Theodosios

  • Author_Institution
    MEMBER, IEEE, Lockheed Palo Alto Research Laboratory, Palo Alto, CA 94304.
  • Issue
    2
  • fYear
    1981
  • fDate
    3/1/1981 12:00:00 AM
  • Firstpage
    144
  • Lastpage
    155
  • Abstract
    The k-syntactic similarity approach is couched in graphical representation terms and its ability to provide global recognition capability while retaining a low time complexity is explored. One potential application domain, that of composite shape decomposition into approximately convex subshapes, is described. This is shown to be equivalent to finding cycles within a particular graph. The approach yields valid decompositions in many cases of interest, and is capable of identifying those cases where additional semantic considerations are necessary for proper analysis. The permissible graph structures representing composite shapes given a reasonable set of relations are determined. Experimental results on nonideal data are given.
  • Keywords
    Computational efficiency; Costs; Noise reduction; Pattern analysis; Pattern recognition; Shape; Smoothing methods; Approximate convex shapes; cycles; graph analysis; shape decomposition; syntactic pattern recognition;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.1981.4767072
  • Filename
    4767072