Modelling Coarseness in Texture Images by Means of Fuzzy Sets (original) (raw)

Abstract

In this paper we model the concept of ”coarseness”, typically used in texture image descriptions, by means of fuzzy sets. Specifically, we relate representative measures of this kind of texture with its presence degree. To obtain these ”presence degrees”, we collect assessments from polls filled by human subjects, performing an aggregation of these assessments by means of OWA operators. Using this collected data, and some statistics as reference set, the membership function corresponding to the fuzzy set ”coarseness” is modelled.

Preview

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Tuceryan, M., Jain, A.: Texture Analysis. In: Chen, C.H., Pau, L.F., Wang, P.S.P. (eds.) The Handbook of Pattern Recognition and Computer Vision, 2nd edn., pp. 207–248 (1998)
    Google Scholar
  2. Shapiro, L.G., Stockman, G.: Image Segmentation. In: Computer Vision, pp. 297–301. Prentice-Hall, Englewood Cliffs (2001)
    Google Scholar
  3. Abbadeni, N., Ziou, D., Wang, S.: Perceptual textural features corresponding to human visual perception. In: Proc. of the Thirteenth Vision Interface Conference, Montreal, Quebec, Canada, pp. 365–372 (2000)
    Google Scholar
  4. Reed, T.R., Buf, J.H.D.: A review of recent texture segmentation and feature extraction techniques. CVGIP: Image Understanding 57(3), 359–372 (1993)
    Article Google Scholar
  5. Shackelford, A.: A hierachical fuzzy classification approach for high-resolution multispectral data over urban areas. IEEE Transactions on Geoscience and Remote Sensing 41(9), 1920–1932 (2003)
    Article Google Scholar
  6. Canny, J.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)
    Article Google Scholar
  7. Yager, R.: On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Transactions on Systems, Man and Cybernetics 18(1), 183–190 (1988)
    Article MATH MathSciNet Google Scholar
  8. Herrera, F., Herrera-Viedma, E.: Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets and Systems 115(1), 67–82 (2000)
    Article MATH MathSciNet Google Scholar

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, C/ Periodista Daniel Saucedo Aranda s/n, 18071, Granada, Spain
    J. Chamorro-Martínez, E. Galán-Perales, D. Sánchez & J. M. Soto-Hidalgo

Authors

  1. J. Chamorro-Martínez
  2. E. Galán-Perales
  3. D. Sánchez
  4. J. M. Soto-Hidalgo

Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK
    Bogdan Gabrys
  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK
    Robert J. Howlett
  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia
    Lakhmi C. Jain

Rights and permissions

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chamorro-Martínez, J., Galán-Perales, E., Sánchez, D., Soto-Hidalgo, J.M. (2006). Modelling Coarseness in Texture Images by Means of Fuzzy Sets. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004\_46

Download citation

Keywords

Publish with us