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Foundations of Computational Intelligence Volume 4 pp 355–375Cite as

Efficient Construction of Image Feature Extraction Programs by Using Linear Genetic Programming with Fitness Retrieval and Intermediate-Result Caching

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 204))

Abstract

This chapter describes a bio-inspired approach for automatic construction of feature extraction programs (FEPs) for a given object recognition problem. The goal of the automatic construction of FEPs is to cope with the difficulties in FEP design. Linear genetic programming (LGP) [4]—a variation of evolutionary algorithms—is adopted. A population of FEPs is constructed from a set of basic image processing operations-which are used as primitive operators (POs), and their performances are optimized in the evolutionary process. Here we describe two techniques that improve the efficiency of the LGP-based program construction. One is to use fitness retrieval—to avoid wasteful evaluations of the programs discovered before. The other one is to use intermediate-result caching—to avoid evaluation of the program-parts which were recently executed. The experimental results show that much computation time of the LGP-based FEP construction can be reduced by using these two techniques.

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Authors and Affiliations

  1. Department of Media Science, Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

    Ukrit Watchareeruetai, Tetsuya Matsumoto, Yoshinori Takeuchi, Hiroaki Kudo & Noboru Ohnishi

Authors
  1. Ukrit Watchareeruetai
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  2. Tetsuya Matsumoto
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  3. Yoshinori Takeuchi
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  4. Hiroaki Kudo
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  5. Noboru Ohnishi
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Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071-2259, Auburn, Washington, USA

    Ajith Abraham

  2. College of Business Administration, Quantitative and Information System Department, Kuwait University, P.O. Box 5486, 13055, Safat, Kuwait

    Aboul-Ella Hassanien

  3. Department of Computer Science, University of São Paulo,SCE - ICMSC - USP, Caixa Postal 668, 13560-970, Sao Carlos, SP, Brazil

    André Ponce de Leon F. de Carvalho

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Watchareeruetai, U., Matsumoto, T., Takeuchi, Y., Kudo, H., Ohnishi, N. (2009). Efficient Construction of Image Feature Extraction Programs by Using Linear Genetic Programming with Fitness Retrieval and Intermediate-Result Caching. In: Abraham, A., Hassanien, AE., de Carvalho, A.P.d.L.F. (eds) Foundations of Computational Intelligence Volume 4. Studies in Computational Intelligence, vol 204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01088-0_15

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  • DOI: https://doi.org/10.1007/978-3-642-01088-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01087-3

  • Online ISBN: 978-3-642-01088-0

  • eBook Packages: EngineeringEngineering (R0)

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