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European Conference on Genetic Programming

EuroGP 2001: Genetic Programming pp 11–22Cite as

Evolving Color Constancy for an Artificial Retina

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2038))

Abstract

Objects retain their color in spite of changes in the wavelength and energy composition of the light they reflect. This phenomenon is called color constancy and plays an important role in computer vision research. We have used genetic programming to automatically search the space of programs to solve the problem of color constancy for an artificial retina. This retina consists of a two dimensional array of elements each capable of exchanging information with its adjacent neighbors. The task of the program is to compute the intensities of the light illuminating the scene. These intensities are then used to calculate the reflectances of the object. Randomly generated color Mondrians were used as fitness cases. The evolved program was tested on artificial Mondrians and natural images.

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Author information

Authors and Affiliations

  1. Lehrstuhl für Informatik II, Universität Würzburg, Am Hubland, 97074, Würzburg, Germany

    Marc Ebner

Authors
  1. Marc Ebner
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Editor information

Editors and Affiliations

  1. School of Computer Science, University of Birmingham, Birmingham

    Julian Miller

  2. Computer Science Institute, University of Lausanne, Lausanne

    Marco Tomassini

  3. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy

    Pier Luca Lanzi

  4. Computer Science and Information Systems, University of Limerick, Limerick

    Conor Ryan

  5. Dipartimento di Tecnologie dell’Informazione, Università degli Studi di Milano, Italy

    Andrea G. B. Tettamanzi

  6. Department of Computer Science, University College London, London

    William B. Langdon

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© 2001 Springer-Verlag Berlin Heidelberg

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Ebner, M. (2001). Evolving Color Constancy for an Artificial Retina. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tettamanzi, A.G.B., Langdon, W.B. (eds) Genetic Programming. EuroGP 2001. Lecture Notes in Computer Science, vol 2038. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45355-5_2

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  • DOI: https://doi.org/10.1007/3-540-45355-5_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41899-3

  • Online ISBN: 978-3-540-45355-0

  • eBook Packages: Springer Book Archive

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