• DocumentCode
    1114681
  • Title

    Decomposition of Two-Dimensional Shapes by Graph-Theoretic Clustering

  • Author

    Shapiro, Linda G. ; Haralick, Robert M.

  • Issue
    1
  • fYear
    1979
  • Firstpage
    10
  • Lastpage
    20
  • Abstract
    This paper describes a technique for transforming a twodimensional shape into a binary relation whose clusters represent the intuitively pleasing simple parts of the shape. The binary relation can be defined on the set of boundary points of the shape or on the set of line segments of a piecewise linear approximation to the boundary. The relation includes all pairs of vertices (or segments) such that the line segment joining the pair lies entirely interior to the boundary of the shape. The graph-theoretic clustering method first determines dense regions, which are local regions of high compactness, and then forms clusters by merging together those dense regions having high enough overlap. Using this procedure on handdrawn colon shapes copied from an X-ray and on handprinted characters, the parts determined by the clustering often correspond well to decompositions that a human might make.
  • Keywords
    Algorithm design and analysis; Associate members; Clustering methods; Colon; Computer science; Gray-scale; Humans; Merging; Piecewise linear approximation; Shape; Clustering; graph-theoretic clustering; relation clustering; shape; shape decomposition; shape matching;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.1979.4766871
  • Filename
    4766871