• DocumentCode
    1382103
  • Title

    An eigendecomposition approach to weighted graph matching problems

  • Author

    Umeyama, Shinji

  • Author_Institution
    Electrotech. Lab., Ibaraki, Japan
  • Volume
    10
  • Issue
    5
  • fYear
    1988
  • fDate
    9/1/1988 12:00:00 AM
  • Firstpage
    695
  • Lastpage
    703
  • Abstract
    An approximate solution to the weighted-graph-matching problem is discussed for both undirected and directed graphs. The weighted-graph-matching problem is that of finding the optimum matching between two weighted graphs, which are graphs with weights at each arc. The proposed method uses an analytic instead of a combinatorial or iterative approach to the optimum matching problem. Using the eigendecompositions of the adjacency matrices (in the case of the undirected-graph-matching problem) or Hermitian matrices derived from the adjacency matrices (in the case of the directed-graph-matching problem), a matching close to the optimum can be found efficiently when the graphs are sufficiently close to each other. Simulation results are given to evaluate the performance of the proposed method
  • Keywords
    eigenvalues and eigenfunctions; graph theory; pattern recognition; Hermitian matrices; adjacency matrices; directed-graph-matching; eigendecomposition; pattern recognition; undirected-graph-matching; weighted graph matching; Arm; Computer science; Computer vision; Head; Image color analysis; Iterative methods; Pattern matching; Pattern recognition; Shape; Spatial databases;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.6778
  • Filename
    6778