Graph matching: a fast algorithm and its evaluation

A graph matching algorithm is illustrated and its performance compared with that of a well known algorithm performing the same task. According to the proposed algorithm the matching process is carried out by using a state space representation: a state represents a partial solution of the matching between two graphs, and a transition between states corresponds to the addition of a new pair of matched nodes. A set of feasibility rules is introduced for pruning states corresponding to partial matching solutions not satisfying the required graph morphism. Results outlining the computational cost reduction achieved by the method are given with reference to a set of randomly generated graphs.

[1]  King-Sun Fu,et al.  Error-Correcting Isomorphisms of Attributed Relational Graphs for Pattern Analysis , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  Mario Vento,et al.  An efficient algorithm for the inexact matching of ARG graphs using a contextual transformational model , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[3]  John E. Hopcroft,et al.  Linear time algorithm for isomorphism of planar graphs (Preliminary Report) , 1974, STOC '74.

[4]  King-Sun Fu,et al.  Subgraph error-correcting isomorphisms for syntactic pattern recognition , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Robert M. Haralick,et al.  Structural Descriptions and Inexact Matching , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  King-Sun Fu,et al.  A distance measure between attributed relational graphs for pattern recognition , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Julian R. Ullmann,et al.  An Algorithm for Subgraph Isomorphism , 1976, J. ACM.

[8]  Alfred V. Aho,et al.  The Design and Analysis of Computer Algorithms , 1974 .