Graph Matching Based on Node Signatures

Authors:
Salim Jouili;Salvatore Tabbone
Affiliations:
University of Nancy 2 - LORIA UMR 7503, BP 239, Vandoeuvre-lès-Nancy Cedex, France 54506;University of Nancy 2 - LORIA UMR 7503, BP 239, Vandoeuvre-lès-Nancy Cedex, France 54506
Venue:
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Year:
2009

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Abstract

We present an algorithm for graph matching in a pattern recognition context. This algorithm deals with weighted graphs, based on new structural and topological node signatures. Using these signatures, we compute an optimum solution for node-to-node assignment with the Hungarian method and propose a distance formula to compute the distance between weighted graphs. The experiments demonstrate that the newly presented algorithm is well suited to pattern recognition applications. Compared with four well-known methods, our algorithm gives good results for clustering and retrieving images. A sensitivity analysis reveals that the proposed method is also insensitive to weak structural changes.