Skip to main content
SpringerLink
Log in
Book cover

International Conference on Pattern Recognition

PAR 1988: Pattern Recognition pp 173–182Cite as

Fuzzy set methods in pattern recognition

  • Fuzzy Set And Pattern Theory
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 301))

Abstract

Dealing with uncertainty is a common problem in pattern recognition. Rarely do object descriptions from different classes fall into totally disjoint regions of feature space. This uncertainty in class definition can be handled in several ways. In this paper we present several approaches to the incorporation of fuzzy set information into pattern recognition. We then introduce a new technique based on the fuzzy integral which combines objective evidence with the importance of that feature set for recognition purposes. In effect, the fuzzy integral performs a local feature selection, in that it attempts to use the strongest measurements first in the object classification. Algorithm performance is illustrated on real and synthetic data sets.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J.T. Tou and R.C. Gonzalez, Pattern Recognition Principles, Reading, MA: Addison-Wesley, 1974.

    Google Scholar 

  2. K.S. Fu, Syntactic Methods in Pattern Recognition, New York: Academic Press, 1974.

    Google Scholar 

  3. A. Kandel, Fuzzy Techniques in Pattern Recognition, New York: John Wiley and Sons, 1982.

    Google Scholar 

  4. J.C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, New York: Plenum Press, 1981.

    Google Scholar 

  5. L.A. Zadeh, "Fuzzy Sets," Inf. Control, Vol. 8, pp. 338–353, 1965.

    Article  Google Scholar 

  6. T.M. Cover and P.E. Hart, "Nearest neighbor pattern classification," IEEE Trans. Inform. Theory, vol. IT-13, pp. 21–27, Jan. 1967.

    Article  Google Scholar 

  7. J. Keller, M. Gray, and J. Givens, Jr., "A fuzzy k-nearest neighbor algorithm," IEEE Trans. Systems, Man, Cybern., Vol. SMC-15, No. 4, July 1985, pp. 580–585.

    Google Scholar 

  8. J. Keller and J. Givens, "Membership function issues in fuzzy pattern recognition," Proc. International Conference on Systems, Man and Cybernetics, Tuscon, 1985, pp. 210–214.

    Google Scholar 

  9. F. Rosenblatt, "The perceptron: A perceiving and recognizing automation," Cornell Univ., Ithaca, NY, Project PARA, Cornell Aeronaut. Lab. Rep., 85-460-1, 1957.

    Google Scholar 

  10. J. Keller, and D. Hunt, "Incorporating fuzzy membership functions into the perceptron algorithm," IEEE Trans. Pattern Anal. Machine Intell., Vol. PAMI-7, No. 6, 1985, pp. 693–699.

    Google Scholar 

  11. M. Sugeno, "Theory of fuzzy integral and its applications," Ph.D. Thesis, Tokyo Institute of Technology, 1974.

    Google Scholar 

  12. L.A. Zadeh, "Calculus of fuzzy restructions," in Fuzzy Sets and Their Applications to Cognitive and Decision Processes, L.A. Zadeh, K.S. Fu, K. Tanaka, and M. Shimura, Eds., London: Academic Press, 1975, pp. 1–26.

    Google Scholar 

  13. H. Qiu and J. Keller, "Multiple Spectral image segmentation using fuzzy techniques", Proc. North American Fuzzy Information Processing Society Workshop, W. Lafayette, IN, 1987, pp. 374–387.

    Google Scholar 

  14. R.A. Fisher, "The use of multiple measurements in taxonomic problems," Ann. Eugenics, Vol. 7, pp. 179–188, 1936.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering, University of Missouri-Columbia, 65211, Columbia, MO

    James M. Keller & Hongjie Qiu

Authors
  1. James M. Keller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hongjie Qiu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

J. Kittler

Rights and permissions

Reprints and permissions

Copyright information

© 1988 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Keller, J.M., Qiu, H. (1988). Fuzzy set methods in pattern recognition. In: Kittler, J. (eds) Pattern Recognition. PAR 1988. Lecture Notes in Computer Science, vol 301. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-19036-8_16

Download citation

  • DOI: https://doi.org/10.1007/3-540-19036-8_16

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19036-3

  • Online ISBN: 978-3-540-38947-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation