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Evolving Local Descriptor Operators through Genetic Programming

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Applications of Evolutionary Computing (EvoWorkshops 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5484))

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Abstract

This paper presents a new methodology based on Genetic Programming that aims to create novel mathematical expressions that could improve local descriptors algorithms. We introduce the RDGP-ILLUM descriptor operator that was learned with two image pairs considering rotation, scale and illumination changes during the training stage. Such descriptor operator has a similar performance to our previous RDGP descriptor proposed in [1], while outperforming the RDGP descriptor in object recognition application. A set of experimental results have been used to test our evolved descriptor against three state-of-the-art local descriptors. We conclude that genetic programming is able to synthesize image operators that outperform significantly previous human-made designs.

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References

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Author information

Authors and Affiliations

  1. Centro de Investigación Científica y de Educación Superior de Ensenada, Ensenada, B.C. 22860, México

    Cynthia B. Perez & Gustavo Olague

Authors
  1. Cynthia B. Perez
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  2. Gustavo Olague
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Editor information

Editors and Affiliations

  1. Department of Animal Production Epidemiology and Ecology, University of Torino, Via Leonardo da Vinci 44, 10095, Grugliasco, Italy

    Mario Giacobini

  2. Quinn School of Business, Belfield, University College Dublin, Dublin 4, Ireland

    Anthony Brabazon

  3. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  4. Dalla Molle Institute for Artificial Intelligence (IDSIA), Gallelria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  5. School of Engineering and Applied Science,Aston Triangle, Aston University, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Complex Adaptive Systems Group, Instituto Tecnológico de Informática, Ciudad PolitŽcnica de la Innovacin, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna Isabel Esparcia-Alcázar

  7. Next Generation Itelligent Networks Research Center (nexGIN RC), National University of Computer and Emerging Sciences (NUCES), Islamabad, Pakistan

    Muddassar Farooq

  8. Faculty of Economics and Social Sciences, Helmut-Schmidt-University, Holstenhofweg 85, 22043, Hamburg, Germany

    Andreas Fink

  9. Department of Informatics Engineering, Polo II - Pinhal de Marrocos, University of Coimbra, 3030 - 290, Coimbra, Portugal

    Penousal Machado

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© 2009 Springer-Verlag Berlin Heidelberg

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Perez, C.B., Olague, G. (2009). Evolving Local Descriptor Operators through Genetic Programming. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_46

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  • DOI: https://doi.org/10.1007/978-3-642-01129-0_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01128-3

  • Online ISBN: 978-3-642-01129-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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