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A Fast Image Analysis Technique for the Line Tracking Robots

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Artifical Intelligence and Soft Computing (ICAISC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6114))

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Abstract

Fast and simplified image processing and analysis methods can be successfully implemented for the robot control algorithms. Statistical methods seem to be very useful for such an approach, mainly because a significant reduction of analysed data is possible. In the paper the use of the fast image analysis based on the Monte Carlo area estimation for the simplified binary representation of the image is analysed and proposed for the mobile robot control. A possible implementation of the proposed method can applied in the line tracking robots and such application has been treated as the basic one for the testing purposes.

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Author information

Authors and Affiliations

  1. Szczecin, Faculty of Electrical Engineering, Chair of Signal Processing and Multimedia Engineering, West Pomeranian University of Technology, 26. Kwietnia 10, 71-126, Szczecin, Poland

    Krzysztof Okarma & Piotr Lech

Authors
  1. Krzysztof Okarma
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  2. Piotr Lech
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Academy of Humanities and Economics in Łódź, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley Initiative in Soft Computing (BISC), 94720-1776, CA

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Louisville, 40292, Louisville, KY

    Jacek M. Zurada

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Okarma, K., Lech, P. (2010). A Fast Image Analysis Technique for the Line Tracking Robots. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artifical Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13232-2_40

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  • DOI: https://doi.org/10.1007/978-3-642-13232-2_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13231-5

  • Online ISBN: 978-3-642-13232-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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