Structural Graph Matching With Polynomial Bounds On Memory and on Worst-Case Effort

A new method of structural graph matching is introduced and compared against an existing method and against the maximum common subgraph. The method is approximate with polynomial bounds on both memory and on the worst-case compute effort. Methods work on arbitrary types of undirected graphs, and tests with strongly regular graphs are included. No node or edge colors are required for matching; the common subgraph is extracted based in structural comparisons only. Monte Carlo test trials included up to 100% additional (noise) nodes that were introduced to both input graphs. Results are possible that recover 100% of the original number of input nodes, and that are within 10% of the number of nodes in the maximum common subgraph. Over 2000 test trials are reported.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Fred W. DePiero
• Keywords: Computer Vision, ICPR 2004, Input Nodes, Maximum Common Subgraph, Structural Graph Matching