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Cartesian Genetic Programming for Image Processing

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Genetic Programming Theory and Practice X

Part of the book series: Genetic and Evolutionary Computation ((GEVO))

Abstract

Combining domain knowledge about both imaging processing and machine learning techniques can expand the abilities of Genetic Programming when used for image processing. We successfully demonstrate our new approach on several different problem domains. We show that the approach is fast, scalable and robust. In addition, by virtue of using off-the-shelf image processing libraries we can generate human readable programs that incorporate sophisticated domain knowledge.

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Notes

  1. 1.

    The competition details can be seen here: http://ipal.i2r.a-star.edu.sg/event/icpr-2012

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Acknowledgements

The authors would like to thank Julian Miller for his help in refining this paper.

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Authors and Affiliations

  1. Dalle Molle Institute for Artificial Intelligence (IDSIA), Manno, Switzerland

    Simon Harding, Jürgen Leitner & Jürgen Schmidhuber

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  1. Simon Harding
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  2. Jürgen Leitner
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  3. Jürgen Schmidhuber
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Correspondence to Simon Harding .

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Editors and Affiliations

  1. Center for the Study of Complex Systems, University of Michigan, West Hall 323, Ann Arbor, 48109, Michigan, USA

    Rick Riolo

  2. Evolved Analytics Europe BVBA, Vossenlaan, Beerse, 2340, Belgium

    Ekaterina Vladislavleva

  3. , Department of Biochemistry and Molecular, The Pennsylvania State University, Wartik Laboratory, University Park, 16802, Pennsylvania, USA

    Marylyn D Ritchie

  4. , Institute for Quantitative, Dartmouth Medical School, Medical Center Drive, Lebanon, 03756, New Hampshire, USA

    Jason H. Moore

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Harding, S., Leitner, J., Schmidhuber, J. (2013). Cartesian Genetic Programming for Image Processing. In: Riolo, R., Vladislavleva, E., Ritchie, M., Moore, J. (eds) Genetic Programming Theory and Practice X. Genetic and Evolutionary Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6846-2_3

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  • DOI: https://doi.org/10.1007/978-1-4614-6846-2_3

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