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International Workshop on Graph-Based Representations in Pattern Recognition

GbRPR 2003: Graph Based Representations in Pattern Recognition pp 118–129Cite as

Theoretical Analysis and Experimental Comparison of Graph Matching Algorithms for Database Filtering

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2726))

Abstract

In structural pattern recognition, an unknown pattern is often transformed into a graph that is matched against a database in order to find the most similar prototype in the database. Graph matching is a powerful yet computationally expensive procedure. If the sample graph is matched against a large database of model graphs, the size of the database is introduced as an additional factor into the overall complexity of the matching process. Database filtering procedures are used to reduce the impact of this additional factor. In this paper we report the results of a basic study on the relation between filtering efficiency and graph matching algorithm performance, using different graph matching algorithms for isomorphism and subgraph-isomorphism.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Bern, Neubrückstrasse 10, CH-3012, Bern, Switzerland

    Christophe Irniger & Horst Bunke

Authors
  1. Christophe Irniger
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  2. Horst Bunke
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of York, York, YO1 5DD, UK

    Edwin Hancock

  2. D.I.I.I.E., Università degli Studi di Salerno, Via Ponte don Melillo, 1, 84084, Fisciano (SA), Italy

    Mario Vento

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© 2003 Springer-Verlag Berlin Heidelberg

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Irniger, C., Bunke, H. (2003). Theoretical Analysis and Experimental Comparison of Graph Matching Algorithms for Database Filtering. In: Hancock, E., Vento, M. (eds) Graph Based Representations in Pattern Recognition. GbRPR 2003. Lecture Notes in Computer Science, vol 2726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45028-9_11

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  • DOI: https://doi.org/10.1007/3-540-45028-9_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40452-1

  • Online ISBN: 978-3-540-45028-3

  • eBook Packages: Springer Book Archive

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