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Matching Attributed Graphs: 2nd-Order Probabilities for Pruning the Search Tree

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Pattern Recognition and Image Analysis (IbPRIA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3523))

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Abstract

A branch-and-bound algorithm for matching Attributed Graphs (AGs) with Second-Order Random Graphs (SORGs) is presented. We show that the search space explored by this algorithm is drastically reduced by using the information of the 2nd-order joint probabilities of vertices of the SORGs. A SORG is a model graph, described elsewhere, that contains 1st and 2nd-order order probabilities of attribute relations between elements for representing a set of AGs compactly. In this work, we have applied SORGs and the reported algorithm to the recognition of real-life objects on images and the results show that the use of 2nd-order relations between vertices is not only useful to decrease the run time but also to increase the correct classification ratio.

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References

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Author information

Authors and Affiliations

  1. Dept. d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Spain

    Francesc Serratosa

  2. Institut de Robòtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Spain

    Alberto Sanfeliu

Authors
  1. Francesc Serratosa
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  2. Alberto Sanfeliu
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Editor information

Editors and Affiliations

  1. Instituto Superior Técnico & Instituto de Sistemas e Robótica,, 1049-001, Lisboa, Portugal

    Jorge S. Marques

  2. ETSI Informática y e Telecomunicación, University of Granada, 18071, Granada, Spain

    Nicolás Pérez de la Blanca

  3. Instituto Superior Técnico, CERENA-Centro de Recursos Naturais e Ambiente, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Pedro Pina

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© 2005 Springer-Verlag Berlin Heidelberg

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Serratosa, F., Sanfeliu, A. (2005). Matching Attributed Graphs: 2nd-Order Probabilities for Pruning the Search Tree. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_17

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  • DOI: https://doi.org/10.1007/11492542_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26154-4

  • Online ISBN: 978-3-540-32238-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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