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Graph Matching Based on Node Signatures

  • Conference paper
Graph-Based Representations in Pattern Recognition (GbRPR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5534))

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.

This work is partially supported by the French National Research Agency project NAVIDOMASS referenced under ANR-06-MCDA-012 and Lorraine region.

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Author information

Authors and Affiliations

  1. University of Nancy 2 - LORIA UMR 7503, BP 239, 54506, Vandoeuvre-lès-Nancy Cedex, France

    Salim Jouili & Salvatore Tabbone

Authors
  1. Salim Jouili
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  2. Salvatore Tabbone
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Editor information

Editors and Affiliations

  1. “Ca’ Foscari” University of Venice, Italy

    Andrea Torsello

  2. Department of Computer Science and Artificial Intelligence, Alicante University, P.O.B. 99, E-03080, Alicante, Spain

    Francisco Escolano

  3. GREYC CNRS UMR 6072, Image Team, Université de Caen Basse-Normandie, 6, Boulevard Maréchal Juin, 14050, Caen Cedex, France

    Luc Brun

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© 2009 Springer-Verlag Berlin Heidelberg

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Jouili, S., Tabbone, S. (2009). Graph Matching Based on Node Signatures. In: Torsello, A., Escolano, F., Brun, L. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2009. Lecture Notes in Computer Science, vol 5534. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02124-4_16

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  • DOI: https://doi.org/10.1007/978-3-642-02124-4_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02123-7

  • Online ISBN: 978-3-642-02124-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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