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Image Segmentation Based on the Indiscernibility Relation

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Rough Sets, Fuzzy Sets and Knowledge Discovery

Part of the book series: Workshops in Computing ((WORKSHOPS COMP.))

Abstract

In this paper, the concepts of indiscernibility relation and approximation space are applied in image segmentation. Specifically, objects can be segmented providing that they are defined to be the connected components with similar gray level; the final segmental image is formed after the region fusion process using the statistical criteria. Then, a generalized method that generates the contour of the objects using the definition of upper and lower approximations is discussed. Thinned image could also be generated from the segmental image.

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References

  1. R. C. Gonzalez and R. E. Woods, Digital Image Processing. New York: Addision-Wesley, 1992.

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  2. A. Mrozek and L. Plonka, “Rough Sets in Image Analysis”, Foundations of Computing and Decision Sciences, vol. 18, no. 3–4, pp. 259–273, 1993.

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  3. Z. Pawlak, “Rough Sets”, International Journal of Computer and Information Science, vol. 11, no. 5, pp. 341–356, 1982.

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  4. M. Pietikainen and D. Harwood, “Edge Information in Colour Images based on Histogram of Differences”, Proceedings of Eighth International Conference on Pattern Recognition. Washington: IEEE Computer Society, October 27–31, Paris, France, pp. 594–596, 1986.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada, S4S 0A2

    Simon Shek Yuen Lau

Authors
  1. Simon Shek Yuen Lau
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    Wojciech P. Ziarko MSc, PhD

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© 1994 British Computer Society

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Lau, S.S.Y. (1994). Image Segmentation Based on the Indiscernibility Relation. In: Ziarko, W.P. (eds) Rough Sets, Fuzzy Sets and Knowledge Discovery. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3238-7_46

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  • DOI: https://doi.org/10.1007/978-1-4471-3238-7_46

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19885-7

  • Online ISBN: 978-1-4471-3238-7

  • eBook Packages: Springer Book Archive

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