Title :
An eigendecomposition approach to weighted graph matching problems
Author_Institution :
Electrotech. Lab., Ibaraki, Japan
fDate :
9/1/1988 12:00:00 AM
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;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on