Skip to main content
SpringerLink
Log in

Multi-valued Fuzzy Spaces for Color Representation

  • Conference paper
Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 443))

  • 777 Accesses

Abstract

This paper proposes two complementary color systems: red-green-blue-white-black and cyan-magenta-yellow-black-white. Both systems belong to the five-valued category and they represent some particular case of neutrosophic information representation. The proposed multi-valued fuzzy spaces are obtained by constructing fuzzy partitions in the unit cube. In the structure of these five-valued representations, the negation, the union and the intersection operators were defined. Next, using the proposed multi-valued representation in the framework of fuzzy clustering algorithm, it results some color image clustering procedure.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Atanassov, K.T.: Remark on a Property of the Intuitionistic Fuzzy Interpretation Triangle. Notes on Intuitionistic Fuzzy Sets 8, 34 (2002)

    MATH  MathSciNet  Google Scholar 

  2. Bhattacharyya, A.: On a measure of divergence between two statistical populations defined by their probability distributions. Bulletin of the Calcutta Mathematical Society 35, 99–109 (1943)

    MATH  MathSciNet  Google Scholar 

  3. Fairchild, M.D.: Color Appearance Models. Addison-Wesley, Reading (1998)

    Google Scholar 

  4. Gonzales, J.C., Woods, R.E.: Digital Image Processing, 1st edn. Addison-Wesley (1992)

    Google Scholar 

  5. Hunter, R.S.: Accuracy, Precision, and Stability of New Photoelectric Color-Difference Meter. JOSA 38(12) (1948), Proceedings of the Thirty Third Annual Meeting of the Optical Society of America

    Google Scholar 

  6. Jain, A.K.: Fundamentals of Digital Image Processing. Prentice Hall, New Jersey (1989)

    MATH  Google Scholar 

  7. MacQueen, J.B.: Some Methods for classification and Analysis of Multivariate Observations. In: Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press, Berkeley (1967)

    Google Scholar 

  8. Michener, J.C., van Dam, A.: A functional overview of the Core System with glossary. ACM Computing Surveys 10, 381–387 (1978)

    Article  Google Scholar 

  9. Ohta, Y., Kanade, T., Sakai, T.: Color information for region segmentation. Computer Graphics and Image Processing 13(3), 222–241 (1980)

    Article  Google Scholar 

  10. Patrascu, V.: New fuzzy color clustering algorithm based on hsl similarity. In: Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress (IFSA 2009), Lisbon, Portugal, pp. 48–52 (2009)

    Google Scholar 

  11. Patrascu, V.: Fuzzy Image Segmentation Based on Triangular Function and Its n-dimensional Extension. In: Nachtegael, M., Van der Weken, D., Kerre, E.E., Philips, W. (eds.) Soft Computing in Image Processing. STUDFUZZ, vol. 210, pp. 187–207. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  12. Patrascu, V.: Fuzzy Membership Function Construction Based on Multi-Valued Evaluation. In: Proceedings of the 10th International FLINS Conference. Uncertainty Modeling in Knowledge Engineering and Decision Making, pp. 756–761. World Scientific Press (2012)

    Google Scholar 

  13. Pătraşcu, V.: Cardinality and Entropy for Bifuzzy Sets. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. CCIS, vol. 80, pp. 656–665. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  14. Patrascu, V.: Multi-valued Color Representation Based on Frank t-norm Properties. In: Proceedings of the 12th Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2008), Malaga, Spain, pp. 1215–1222 (2008)

    Google Scholar 

  15. Smarandache, F.: Neutrosophy. / Neutrosophic Probability, Set, and Logic. American Research Press, Rehoboth (1998)

    MATH  Google Scholar 

  16. Smarandache, F.: Definiton of neutrosophic logic - a generalization of the intuitionistic fuzzy logic. In: Proceedings of the Third Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2003, Zittau, Germany, pp. 141–146 (2003)

    Google Scholar 

  17. Smarandache, F.: Generalization of the Intuitionistic Fuzzy Logic to the Neutrosophic Fuzzy Set. International Journal of Pure and applied Mathematics 24(3), 287–297 (2005)

    MATH  MathSciNet  Google Scholar 

  18. Smith, A.R.: Color Gamut transform pairs. Computer Graphics SIGGRAPH 1978 Proceedings 12(3), 12–19 (1978)

    Article  Google Scholar 

  19. Zadeh, L.A.: Fuzy sets. Inf. Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tarom Information Technology, Bucharest, Romania

    Vasile Patrascu

Authors
  1. Vasile Patrascu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University Montpellier 2, LIRMM - CNRS UMR 5506, 161, Rue Ada, 34392, Montpellier Cedex 5, France

    Anne Laurent

  2. LIRMM, UMR CNRS/Universite Montpellier II, 161 rue Ada, 34392, Montpellier cedex 5, France

    Olivier Strauss

  3. UPMC Univ. Paris 06, CNRS UMR 7606, LIP6, F-75005, Paris, France

    Bernadette Bouchon-Meunier

  4. Dept. of Information Systems, Iona College, 710 North Ave, 10801, New Rochelle, NY, USA

    Ronald R. Yager

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Patrascu, V. (2014). Multi-valued Fuzzy Spaces for Color Representation. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-08855-6_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08855-6_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08854-9

  • Online ISBN: 978-3-319-08855-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation