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Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition pp 49–65Cite as

A Genetic Programming Approach to the Design of Interest Point Operators

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 256))

Abstract

Recently, the detection of local image feature has become an indispensable process for many image analysis or computer vision systems. In this chapter, we discuss how Genetic Programming (GP), a form of evolutionary search, can be used to automatically synthesize image operators that detect such features on digital images. The experimental results we review, confirm that artificial evolution can produce solutions that outperform many man-made designs. Moreover, we argue that GP is able to discover, and reuse, small code fragments, or building blocks, that facilitate the synthesis of image operators for point detection. Another noteworthy result is that the GP did not produce operators that rely on the auto-correlation matrix, a mathematical concept that some have considered to be the most appropriate to solve the point detection task. Hence, the GP generates operators that are conceptually simple and can still achieve a high performance on standard tests.

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Author information

Authors and Affiliations

  1. Proyecto Evovisión, Departamento de Ciencias de la Computación, División de Física Aplicada, Centro de Investigación Científica y de Educación Superior de Ensenada, Km. 107 Carretera Tijuana-Ensenada, 22860, Ensenada, BC, México

    Gustavo Olague

  2. Instituto Tecnológico de Tijuana, Av. Tecnolǵico, Fracc. Tomás Aquino, Tijuana, B.C., México

    Leonardo Trujillo

Authors
  1. Gustavo Olague
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  2. Leonardo Trujillo
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Tijuana Institute of Technology, P.O. Box 4207, 91909, Chula Vista, CA, USA

    Patricia Melin

  2. Systems Research Institute, Newelska, Polish Academy of Sciences, 601-447, Warszawa, Poland

    Janusz Kacprzyk

  3. Dept. Electrical and Computer Engineering, University of Alberta, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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© 2009 Springer-Verlag Berlin Heidelberg

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Olague, G., Trujillo, L. (2009). A Genetic Programming Approach to the Design of Interest Point Operators. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition. Studies in Computational Intelligence, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04516-5_3

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  • DOI: https://doi.org/10.1007/978-3-642-04516-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04515-8

  • Online ISBN: 978-3-642-04516-5

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