Movatterモバイル変換

[0]ホーム
URL:

Skip to main content

Advertisement

Springer Nature Link
Log in

Robust Color Classification Using Fuzzy Reasoning and Genetic Algorithms in RoboCup Soccer Leagues

  • Conference paper

Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 5001))

Included in the following conference series:

Abstract

Color segmentation is typically the first step of vision processing for a robot operating in a color coded environment, like RoboCup soccer, and many object recognition modules rely on that, in this paper we present a method for color segmentation that is based on fuzzy logic. Fuzzy sets are defined on the H, S and L components of the HSL color space and provide a fuzzy logic model that aims to follow the human intuition of color classification. The membership functions used for the fuzzy inference are optimized by genetic algorithms. The method requires the setting of only a few parameters and has been proved to be very robust to noise and light variations, allowing for setting parameters only once. The approach has been implemented on MRL middle size robots, and successfully experimented in the numbers of the friendly matches of the Middle size in the 2006’s games.

Similar content being viewed by others

Keywords

References

  1. Lovell, N.: Illumination independent object recognition. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  2. Bezdek, J.C., Keller, J., Raghu, K., Pal, N.H.: Fuzzy modelsand algorithms fo. Pattern recognition and image processing. Kluwer Academic Pubkishers, Boston (1999)

    Google Scholar 

  3. Tolias, Y.A., Panas, S.M.: On applying spatial constraints in fuzzy image clustering using a fuzzy rulebased system. IEEE Signal Processing Letters 5, 245–247 (1998)

    Article  Google Scholar 

  4. Bezdek, J.C.: Patten recognition with fuzzy objective function algorithms, pp. 65–85. Plenum Press, New York (1981)

    Google Scholar 

  5. Krishnapuram, R., Keller, J.M.: A possibilistic approach to clustering. IEEE Pans, Fuzzy Systems 1, 98–110 (1993)

    Article  Google Scholar 

  6. Makrogiannis, S., Eeanomou, G., Fatopoulos, S.: A fuzzy dissimilarity function for region based segmentation of color images. int. j. pattern recogn. artif. Intell. 15, 255–267 (2001)

    Article  Google Scholar 

  7. Roire, J.: Les noms des couleurs, Pour la science, Hors sfierie, no. 27 (2000)

    Google Scholar 

  8. Truck, I.: Approaches symbolique et floue des modificateurs linguistiques et leur lien avec ’aggregation, Ph.D. Thesis, Universit_e de Reims Champagne-Ardenne, France (December 2002)

    Google Scholar 

  9. Truck, I., Akdag, H., Borgi, A.: A Symbolic Approach for Colorimetric Alterations. In: Proceedings of EUSFLAT 2001, Leicester, England, pp. 105–108 (September 2001)

    Google Scholar 

  10. Herrera, F., Martinez, L.: A model based on linguistic two-tuples for dealing with multigranularity hierarchical linguistic contexts in multiexpert decision-making. IEEE transactions on Systems, Man and Cybernetics, Part B 31(2), 227–234 (2001)

    Article  Google Scholar 

  11. Bouchon-Meunier, B.: La Logique Floue et ses Applications. Addison-Wesley (1995)

    Google Scholar 

  12. Truck, I., Akdag, H., Borgi, A.: Using Fuzzy modifiers in Colorimetery. In: Proceedings of the 5th World Multi conference on Systemic, Cybernetics and Informatics, SCI 2001, Orlando, Florida, USA, pp. 472–477 (2001)

    Google Scholar 

  13. Sakurai, M., Kurihara, Y.: Color Classification Using Fuzzy Inference and Genetic Algorithm. In: Proc. IEEE int. conf. on Fuzzy systems, vol. 3, pp. 1975–1978 (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Mechatronic Research Labratory Dept. of Electrical and Computer Engineering, Azad University, Qazvin, Iran

    Alireza Kashanipour

  2. Dept. of Electrical Engineering, Sahand University of Technolegy, Tabriz, Iran

    Amir Reza Kashanipour, Nargess Shamshiri Milani, Peyman Akhlaghi & Kaveh Khezri Boukani

Authors
  1. Alireza Kashanipour

    You can also search for this author inPubMed Google Scholar

  2. Amir Reza Kashanipour

    You can also search for this author inPubMed Google Scholar

  3. Nargess Shamshiri Milani

    You can also search for this author inPubMed Google Scholar

  4. Peyman Akhlaghi

    You can also search for this author inPubMed Google Scholar

  5. Kaveh Khezri Boukani

    You can also search for this author inPubMed Google Scholar

Editor information

Ubbo Visser Fernando Ribeiro Takeshi Ohashi Frank Dellaert

Rights and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kashanipour, A., Kashanipour, A.R., Milani, N.S., Akhlaghi, P., Boukani, K.K. (2008). Robust Color Classification Using Fuzzy Reasoning and Genetic Algorithms in RoboCup Soccer Leagues. In: Visser, U., Ribeiro, F., Ohashi, T., Dellaert, F. (eds) RoboCup 2007: Robot Soccer World Cup XI. RoboCup 2007. Lecture Notes in Computer Science(), vol 5001. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68847-1_59

Download citation

Publish with us

[8]ページ先頭
©2009-2025 Movatter.jp