Skip to main content
SpringerLink
Log in

New Pattern Recognition Tools Based on Fuzzy Logic for Image Understanding

  • Chapter
Book cover Soft Computing for Image Processing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 42))

Abstract

We present in this paper some applications of fuzzy logic tools for pattern recognition problems in image understanding. This includes pattern recognition and object recognition in particular. It is shown that fuzzy integrals and fuzzy rules provide powerful tools for solving such problems.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J.C. Bezdek (1981). Pattern recognition with fuzzy objective function algorithms. Plenum Press, New York.

    Book  MATH  Google Scholar 

  2. J.C. Bezdek (1993). A review of probabilistic, fuzzy and neural models for pattern recognition. J. of Intelligent and Fuzzy Systems, 1:1–25.

    Google Scholar 

  3. J.C. Bezdek and S.K. Pal (eds) (1992). Fuzzy Models for Pattern Recognition. IEEE Press.

    Google Scholar 

  4. G. Choquet (1953). Theory of capacities. Annales de I’Institut Fourier, 5:131–295.

    Article  MathSciNet  Google Scholar 

  5. D. Denneberg (1994). Non–Additive Measure and Integral. Kluwer Academic.

    Book  MATH  Google Scholar 

  6. D. Dubois and H. Prade (1985). Possibility Theory. Plenum Press.

    MATH  Google Scholar 

  7. D. Dubois and H. Prade (1991). Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions. Fuzzy Sets and Systems, 40:143–202.

    Article  MathSciNet  MATH  Google Scholar 

  8. D. Dubois and H. Prade (1992). Gradual inference rules in approximate reasoning. Information Sciences, 61:103–122.

    Article  MathSciNet  MATH  Google Scholar 

  9. J. Figue, M. Grabisch, and M.–P. Charbonnel (1999). A method for still image interpretation relying on a multi–algorithms fusion scheme, application to human face characterization. Fuzzy Sets and Systems, 103:317–337.

    Article  Google Scholar 

  10. J Gasos and A. Ralescu (1995). Towards a linguistic instructions based navigation support system — using environment information for guiding scene interpretation. In Int. Joint Conf. of the 4th IEEE Int. Conf. on Fuzzy Sys—tems and the 2nd Int. Fuzzy Engineering Symp., pages 1261–1266, Yokohama, Japan.

    Google Scholar 

  11. M. Grabisch (1994). Fuzzy integrals as a generalized class of order filters. In European Symposium on Satellite Remote Sensing, Roma, Italy.

    Google Scholar 

  12. M. Grabisch (1995). A new algorithm for identifying fuzzy measures and its application to pattern recognition. In Int. Joint Conf. of the 4th IEEE Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symposium, pages 145–150, Yokohama, Japan.

    Google Scholar 

  13. M. Grabisch, J. Figue, and M.P. Charbonnel (1996). Analysis and modeling of face images. In Jfth Int. Conf. on Soft Computing, pages 761–764, Iizuka, Japan.

    Google Scholar 

  14. M. Grabisch and F. Huet (1996). Texture recognition by Choquet integral filters. In 6th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge–Based Systems (IPMU), pages 1325–1330, Granada, Spain.

    Google Scholar 

  15. M. Grabisch, H.T. Nguyen, and E.A. Walker (1995). Fundamentals of Uncer– tainty Calculi, with Applications to Fuzzy Inference. Kluwer Academic.

    Google Scholar 

  16. M. Grabisch and M. Schmitt (1995). Mathematical morphology, order filters and fuzzy logic. In Int. Joint Conf. of the 4th IEEE Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symposium, pages 2103–2108, Yokohama, Japan.

    Google Scholar 

  17. M. Grabisch and M. Sugeno (1992). Multi–attribute classification using fuzzy integral. In 1st IEEE Int. Conf. on Fuzzy Systems, pages 47–54, San Diego, CA.

    Google Scholar 

  18. M. Kawade (1995). Object recognition system in a dynamic environment. In Int. Joint Conf. of the 4th IEEE Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symp., pages 1285–1290, Yokohama, Japan.

    Google Scholar 

  19. J.M. Keller, P.D. Gader, and A.K. Hocaoglu (l999). Fuzzy integrals in image processing and recognition. In M. Grabisch, T. Murofushi, and M. Sugeno, editors, Fuzzy Measures and Integrals — Theory and Applications. Physica Verlag, to appear.

    Google Scholar 

  20. J.M. Keller, M. R. Gray, and jr. J. A. Givens (1985). A fuzzy fc–nearest neighbor algorithm. IEEE Trans, on Syst, Man & Cyb., 15(4):580–585.

    Article  Google Scholar 

  21. A. Kosako and A.L. Ralescu (1995). Feature based parametric eigenspace method for object extraction. In Int. Joint Conf. of the 4th IEEE Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symp., pages 1273–1278, Yokohama, Japan.

    Google Scholar 

  22. W. Liu and M. Sugeno (1997). Object understanding using case–based reasoning with fuzzy attributes graphs and genetic algorithms. J. of Japan Society for Fuzzy Theory and Systems, 9(l):71–80.

    Google Scholar 

  23. D.P. Mandal, C.A. Murthy, and S.K. Pal (1992). Formulation of a multivalued recognition system. IEEE Tr. on Systems, Man and Cybernetics, 22:607–620.

    Article  MATH  Google Scholar 

  24. L. Mascarilla and J. Desachy (1997). Fuzzy rules extraction and redundancy elimination. Int. J. of Intelligent Systems, 12:793–817.

    Article  Google Scholar 

  25. K. Miyajima and A. Ralescu (1992). Fuzzy logic approach to modelbased image analysis. Technical Report TR–4K–004E, LIFE, Yokohama, Japan.

    Google Scholar 

  26. K. Miyajima and A. Ralescu (1993). Modeling of natural objects including fuzziness and application to image understanding. In 2nd IEEE Congr. On Fuzzy Systems, pages 1049–1054, San Francisco, CA.

    Google Scholar 

  27. K. Miyajima and A. Ralescu (1994). Spatial relations in 2D segmented images: representations and recognition. Fuzzy Sets and Systems, 65:225–236.

    Article  Google Scholar 

  28. S.K. Pal and D.K. Dutta Majumder (1986). Fuzzy mathematical approach to pattern recognition. Wiley Eastern Ltd.

    MATH  Google Scholar 

  29. E. Pap (1995). Null–Additive Set Functions. Kluwer Academic.

    MATH  Google Scholar 

  30. W. Pedrycz (1990). Fuzzy sets in pattern recognition: methodology and methods. Pattern Recognition, 23(1/2):121–146.

    Article  Google Scholar 

  31. A. Pentland, B. Moghaddam, and T. Starner (1994). View–based and modular eigenspaces for face recognition. Proceeding of IEEE, pages 84–91.

    Google Scholar 

  32. A.L. Ralescu and J.G. Shanahan (1995). Fuzzy perceptual grouping in image understanding. In Int. Joint Conf. of the 4th IEEE Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symp., pages 1267–1272, Yokohama, Japan.

    Google Scholar 

  33. L. Roux and J. Desachy (1996). Multisources information fusion application for satellite image classification. In D. Dubois, H. Prade, and R. Yager, editors, Fuzzy Information Engineering — A Guided Tour of Applications, pages 111–121. J. Wiley.

    Google Scholar 

  34. E. H. Ruspini (1969). A new approach to clustering. Inform. Control, 15(1):22–32.

    Article  MATH  Google Scholar 

  35. M. Sugeno (1974). Theory of fuzzy integrals and its applications. PhD thesis, Tokyo Institute of Technology.

    Google Scholar 

  36. H. Tahani and J.M. Keller (1990). Information fusion in computer vision using the fuzzy integral. IEEE Tr. on Systems, Man, and Cybernetics, 20(3) :733–741.

    Article  Google Scholar 

  37. E.H. Zahzah and J. Desachy (1993). Symbolic and numeric data management in a geographical information system: a fuzzy neural network approach. In 8th Austrian Artificial Intelligence Conference FLAV93, volume 695 of Lecture Note in Artificial Intelligence, Linz, Austria. Springer Verlag.

    Google Scholar 

  38. W. Zhang and M. Sugeno (1993. A fuzzy approach to scene understanding. In 2nd IEEE Congr. on Fuzzy Systems, pages 564–569, San Francisco, CA.

    Google Scholar 

  39. W. J. Zhang and A. Ralescu (1994). Object recognition based on pattern features. In Proc. of Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU’94), pages 1133–1138, Paris, France.

    Google Scholar 

  40. W.J. Zhang and A. Ralescu (1995). Visual pattern based approach to object recognition. In Int. Joint Conf. of the Ifih IEEE Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symp., pages 1279–1284, Yokohama, Japan.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Thomson-CSF, Corporate Research Laboratory Domaine de Corbeville, Orsay, France

    Michel Grabisch

Authors
  1. Michel Grabisch
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Calcutta, 700035, India

    Sankar K. Pal , Ashish Ghosh  & Malay K. Kundu ,  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Grabisch, M. (2000). New Pattern Recognition Tools Based on Fuzzy Logic for Image Understanding. In: Pal, S.K., Ghosh, A., Kundu, M.K. (eds) Soft Computing for Image Processing. Studies in Fuzziness and Soft Computing, vol 42. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1858-1_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-7908-1858-1_12

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2468-1

  • Online ISBN: 978-3-7908-1858-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation