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Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems

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Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2134))

Abstract

The interest of graph matching techniques in the pattern recognition field is increasing due to the versatility of representing knowledge in the form of graphs. However, the size of the graphs as well as the number of attributes they contain can be too high for optimization algorithms. This happens for instance in image recognition, where structures of an image to be recognized need to be matched with a model defined as a graph.

In order to face this complexity problem, graph matching can be regarded as a combinatorial optimization problem with constraints and it therefore it can be solved with evolutionary computation techniques such as Genetic Algorithms (GAs) and Estimation Distribution Algorithms (EDAs).

This work proposes the use of EDAs, both in the discrete and continuous domains, in order to solve the graph matching problem. As an example, a particular inexact graph matching problem applied to recognition of brain structures is shown. This paper compares the performance of these two paradigms for their use in graph matching.

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Author information

Authors and Affiliations

  1. Department of Computer Architecture and Technology, University of the Basque Country, San Sebastian, Spain

    Endika Bengoetxea

  2. Department of Computer Science and Artificial Intelligence, University of the Basque Country, San Sebastian, Spain

    Pedro Larrañaga

  3. Department of Signal and Image Processing Ecole Nationale Supérieure des Télécommunications, CNRS URA 820, Paris, France

    Isabelle Bloch & Aymeric Perchant

Authors
  1. Endika Bengoetxea
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  2. Pedro Larrañaga
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  3. Isabelle Bloch
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  4. Aymeric Perchant
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Editor information

Editors and Affiliations

  1. Instituto de Telecomunicacoes and Instituto Superior Tecnico, 1049-001, Lisboa, Portugal

    Mário Figueiredo

  2. INRIA, 2004 Route des Lucioles, 06902 Sophia-Antipolis cedex, France

    Josiane Zerubia

  3. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA

    Anil K. Jain

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© 2001 Springer-Verlag Berlin Heidelberg

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Bengoetxea, E., Larrañaga, P., Bloch, I., Perchant, A. (2001). Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems. In: Figueiredo, M., Zerubia, J., Jain, A.K. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2001. Lecture Notes in Computer Science, vol 2134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44745-8_30

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  • DOI: https://doi.org/10.1007/3-540-44745-8_30

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42523-6

  • Online ISBN: 978-3-540-44745-0

  • eBook Packages: Springer Book Archive

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