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Grey-Scale Morphology Based on Fuzzy Logic

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Abstract

There exist several methods to extend binary morphology to grey-scale images. One of these methods is based on fuzzy logic and fuzzy set theory. Another approach starts from the complete lattice framework for morphology and the theory of adjunctions. In this paper, both approaches are combined. The basic idea is to use (fuzzy) conjunctions and implications which are adjoint in the definition of dilations and erosions, respectively. This gives rise to a large class of morphological operators for grey-scale images. It turns out that this class includes the often used grey-scale Minkowski addition and subtraction.

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References

  1. I. Bloch and H. Maitre, “Fuzzy mathematical morphology,” Annals of Mathematics and Artificial Intelligence, Vol. 10, pp. 55–84, 1994.

    Google Scholar 

  2. I. Bloch and H. Maitre, “Fuzzy mathematical morphologies: A comparative study,” Pattern Recognition, Vol. 28, No. 9, pp. 1341–1387, 1995.

    Google Scholar 

  3. B. De Baets. “Fuzzy morphology: A logical approach,” in Uncertainty Analysis in Engineering and Science: Fuzzy Logic, Statistics, and Neural Network Approach, B.M. Ayyub and M.M. Gupta (Eds.), Kluwer Academic Publishers: Norwell, 1997, pp. 53–67.

    Google Scholar 

  4. B. DeBaets and E. Kerre, “The fundamentals of fuzzy mathematical morphology part 1: Basic concepts,” International Journal of General Systems, Vol. 23, pp. 155–171, 1995.

    Google Scholar 

  5. V. Goetcherian, “From binary to grey tone image processing using fuzzy logic concepts,” Pattern Recognition, Vol. 12, pp. 7–15, 1980.

    Google Scholar 

  6. H.J.A.M. Heijmans, “Theoretical aspects of gray-level morphology, “IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, pp. 568–582, 1991.

    Google Scholar 

  7. H.J.A.M. Heijmans, “A note on the umbra transform in gray-scale morphology,” Pattern Recognition Letters, Vol. 14, pp. 877–881, 1993.

    Google Scholar 

  8. H.J.A.M. Heijmans, “Morphological Image Operators, Academic Press: Boston, 1994.

    Google Scholar 

  9. E. Kerre and M. Nachtegael, Fuzzy Techniques in Image Processing: Techniques and Applications. Studies in Fuzziness and Soft Computing, Vol. 52. Physica Verlag: Heidelberg 2000.

    Google Scholar 

  10. G.J. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall: Upper Saddle River, 1995.

    Google Scholar 

  11. R. Kruse, J. Gebhardt, and F. Klawonn, Foundations of Fuzzy Systems, John Wiley &; Sons: England, 1994.

    Google Scholar 

  12. P. Maragos and R.D. Ziff, “Threshold superposition in morphological image analysis systems,” IEEE Transactions on Pattern Analysis andMachine Intelligence,Vol. 12, pp. 498–504, 1990.

    Google Scholar 

  13. G. Matheron, Random Sets and Integral Geometry, John Wiley &; Sons: New York, 1975.

    Google Scholar 

  14. M. Nachtegael, and E. Kerre, “Connections between binary, grey-scale and fuzzy mathematical morphology,” Fuzzy Sets and Systems, Vol. 129, pp. 73–86, 2001.

    Google Scholar 

  15. H.T. Nguyen and E.A. Walker, A First Course in Fuzzy Logic, 2nd edn., Chapman &; Hall/CRC: Boca Raton, Florida, 1994.

    Google Scholar 

  16. C. Ronse, “Why mathematical morphology needs complete lattices,” Signal Processing, Vol. 21, pp. 129–154, 1990.

    Google Scholar 

  17. J. Serra, Image Analysis and Mathematical Morphology, Academic Press: London, 1982.

    Google Scholar 

  18. J. Serra (Ed.), Image Analysis and Mathematical Morphology. II: Theoretical Advances, Academic Press: London, 1988.

    Google Scholar 

  19. D. Sinha and E.R. Dougherty, “Fuzzy mathematical morphology,” Journal of Visual Communication and Image Representation, Vol. 3, No. 3, pp. 286–302, 1992.

    Google Scholar 

  20. D. Sinha and E.R. Dougherty, “Fuzzification of set inclusion: Theory and applications,” Fuzzy Sets and Systems, Vol. 55, pp. 15–42, 1993.

    Google Scholar 

  21. P. Soille, Morphological Image Analysis, Springer-Verlag: Berlin, 1999.

    Google Scholar 

  22. S.R. Sternberg, “Grayscale morphology,” Computer Vision, Graphics and Image Processing, Vol. 35, pp. 333–355, 1986.

    Google Scholar 

  23. L.A. Zadeh, “Fuzzy sets,” Information and Control, Vol. 8, pp. 338–353, 1965.

    Google Scholar 

  24. H.J. Zimmerman, Fuzzy Set Theory and its Applications, Academic Press: Boston, 1991.

    Google Scholar 

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Deng, TQ., Heijmans, H.J. Grey-Scale Morphology Based on Fuzzy Logic. Journal of Mathematical Imaging and Vision 16, 155–171 (2002). https://doi.org/10.1023/A:1013999431844

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