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Published Articles >> Table of Contents >> Abstract
September 1988 (Vol. 10, No. 5)
pp. 695-703
An Eigendecomposition Approach to Weighted Graph Matching Problems
S. Umeyama
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.6778
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| Abstract |
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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.
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References
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Additional Information
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Index Terms- pattern recognition; eigendecomposition; weighted graph matching; adjacency matrices; undirected-graph-matching; Hermitian matrices; directed-graph-matching; eigenvalues and eigenfunctions; graph theory; pattern recognition
Citation:
S. Umeyama,
"An Eigendecomposition Approach to Weighted Graph Matching Problems,"
IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 10,
no. 5,
pp. 695-703,
Sept.,
1988
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