Skip to main content

Fuzzy Sets Theory Based Region Merging for Robust Image Segmentation

  • Conference paper
Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

Included in the following conference series:

Abstract

A fuzzy set theory based region merging approach is presented to tackle the issue of oversegmentation from the watershed algorithm, for achieving robust image segmentation. A novel hybrid similarity measure is proposed as the merging criterion, based on the region-based similarity and the edge-based similarity. Both similarities are obtained using the fuzzy set theory. To adaptively adjust the influential degree of each similarity to region merging, a simple but effective weighting scheme is employed with the weight varying as region merging proceeds. The proposed approach has been applied to various images, including gray-scale images and color images. Experimental results have demonstrated that the proposed approach produces quite robust segmentations.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Haris, K., Efstratiadis, S.N., Maglaveras, N., Katsaggelo, A.K.: Hybrid image segmentation using watersheds and fast region merging. IEEE Trans. Image Processing. 7, 1684–1699 (1998)

    Article  Google Scholar 

  2. Navon, E., Miller, O., Averbuch, A.: Color image segmentation based on adaptive local thresholds. Image and Vision Computing 23, 69–85 (2005)

    Article  Google Scholar 

  3. Vincent, L., Soille, P.: Watersheds in digital space: an efficient algorithm based on immersion simulations. IEEE Trans. PAMI. 13, 583–598 (1991)

    Google Scholar 

  4. Kim, J.B., Kim, H.J.: Multiresolution-based watersheds for efficient image segmentation. Pattern Recognition Letters 24, 473–488 (2003)

    Article  Google Scholar 

  5. Zhu, H., Basir, O., Karray, F.: Fuzzy integral based region merging for watershed image segmentation. Proc. 10th IEEE Int. Conf. on Fuzzy Systems. 1, 27–30 (2001)

    Google Scholar 

  6. Chu, C., Aggarwal, J.K.: The integration of image segmentation maps using region and edge information. IEEE Trans. PAMI. 15, 1241–1252 (1993)

    Google Scholar 

  7. Canny, J.: A computational approach to edge detection. IEEE Trans. PAMI 8, 679–698 (1986)

    Google Scholar 

  8. Ballard, D., Brown, C.: Computer Vision. Prentice-Hall, Englewood Cliffs (1982)

    Google Scholar 

  9. Chen, Y., Wang, J.Z.: A region-based fuzzy feature matching approach to content-based image retrieval. IEEE Trans. PAMI. 24, 1252–1267 (2002)

    Google Scholar 

  10. Van der Weken, D., Nachtegael, M., Kerre, E.E.: Using similarity and homogeneity for the comparison of images. Image and Vision Computing 22, 695–702 (2004)

    Article  Google Scholar 

  11. Pal, S.K., Ghosh, A.: Index of area coverage of fuzzy image subsets and object extraction. Pattern Recognition Letters 11, 831–841 (1990)

    Article  MATH  Google Scholar 

  12. Tizhoosh, H.R.: Fuzzy Image Processing: Introduction in Theory and Practice. Springer, Heidelberg (1997)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhu, H., Basir, O. (2005). Fuzzy Sets Theory Based Region Merging for Robust Image Segmentation. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_55

Download citation

  • DOI: https://doi.org/10.1007/11539506_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics