Abstract
Interval-valued fuzzy mathematical morphology is an extension of classical fuzzy mathematical morphology, which is in turn one of the extensions of binary morphology to greyscale morphology. The uncertainty that may exist concerning the grey value of a pixel due to technical limitations or bad recording circumstances, is taken into account by mapping the pixels in the image domain onto an interval to which the pixel’s grey value is expected to belong instead of one specific value. Such image representation corresponds to the representation of an interval-valued fuzzy set and thus techniques from interval-valued fuzzy set theory can be applied to extend greyscale mathematical morphology. In this paper, we study the decomposition of the interval-valued fuzzy morphological operators. We investigate in which cases the [α 1,α 2]-cuts of these operators can be written or approximated in terms of the corresponding binary operators. Such conversion into binary operators results in a reduction of the computation time and is further also theoretically interesting since it provides us a link between interval-valued fuzzy and binary morphology.
Similar content being viewed by others
References
Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, San Diego (1982)
Haralick, R.M., Sternberg, R.S., Zhuang, X.: Image analysis using mathematical morphology. IEEE Trans. Pattern Anal. Mach. Intell. 9(4), 532–550 (1987)
De Baets, B.: Fuzzy morphology: a logical approach. In: Ayyub, B.M., Gupta, M.M. (eds.) Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach, pp. 53–67. Kluwer Academic, Dordrecht (1997)
Sussner, P., Valle, M.E.: Classification of fuzzy mathematical morphologies based on concepts of inclusion measure and duality. J. Math. Imaging Vis. 32(2), 139–159 (2008)
Popov, A.T.: General approach for fuzzy mathematical morphology. In: Proceedings of ISMM 2007 (International Symposium on Mathematical Morphology), pp. 39–47 (2007)
Bloch, I.: Mathematical morphology on bipolar fuzzy sets. In: Proceedings of ISMM 2007 (International Symposium on Mathematical Morphology), pp. 3–4 (2007)
Bloch, I.: Dilation and erosion of spatial bipolar fuzzy sets. In: Lecture Notes in Artificial Intelligence (Proceedings of WILF 2007), vol. 4578, pp. 385–393 (2007)
Nachtegael, M., Sussner, P., Mélange, T., Kerre, E.E.: Some aspects of interval-valued and intuitionistic fuzzy mathematical morphology. In: Proceedings of IPCV 2008 (International Conference on Image Processing, Computer Vision and Pattern Recognition) (2008)
Nachtegael, M., Sussner, P., Mélange, T., Kerre, E.E.: Modelling numerical and spatial uncertainty in grayscale image capture using fuzzy set theory. In: Proceedings of NASTEC 2008, pp. 15–22 (2008)
Sambuc, R.: Fonctions Φ-floues. Application à l’aide au diagnostic en pathologie thyroidienne. Ph.D. thesis, Univ. Marseille, France (1975)
Zadeh, L.: Fuzzy Sets. Inf. Control 8, 338–353 (1965)
Deschrijver, G., Kerre, E.E.: On the relationship between some extensions of fuzzy set theory. Fuzzy Sets Syst. 133, 227–235 (2003)
Cabrera, S.D., Iyer, K., Xiang, G., Kreinovich, V.: On inverse halftoning: computational complexity and interval computations. In: Proceedings of CISS 2005 (39th Conference on Information Sciences and Systems), The John Hopkins University, paper 164 (2005)
Brito, A.E., Kosheleva, O.: Interval+image=wavelet: for image processing under interval uncertainty, wavelets are optimal. Reliab. Comput. 4(4), 771–783 (1998)
Barrenechea, E.: Image processing with interval-valued fuzzy sets—edge detection—contrast. Ph.D. thesis, Public university of Navarra (2005)
Palma, G., Bloch, I., Muller, S.: Fuzzy connected filters for fuzzy gray scale images. In: Proceedings of IPMU’08 (Information Processing and Management of Uncertainty in Knowledge-Based Systems), pp. 667–674 (2008)
Atanassov, K.: Intuitionistic Fuzzy Sets. Physica Verlag, Heidelberg (1999)
Deschrijver, G., Cornelis, C.: Representability in interval-valued fuzzy set theory. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 15(3), 345–361 (2007)
Bloch, I.: Duality vs. adjunction for fuzzy mathematical morphology and general form of fuzzy erosions and dilations. Fuzzy Sets Syst. 160, 1858–1867 (2009)
Nachtegael, M., Kerre, E.E.: Connections between binary, gray-scale and fuzzy nathematical morphology. Fuzzy Sets Syst. 124, 73–86 (2001)
Wang, G., Li, X.: The applications of interval-valued fuzzy numbers and interval-distribution numbers. Fuzzy Sets Syst. 98, 331–335 (1998)
Klement, E.P., Mesiar, R., Pap, E.: Triangular Norms. Kluwer Academic, Dordrecht (2000)
Nachtegael, M., Kerre, E.E.: Decomposing and constructing of fuzzy morphological operations over alpha-cuts: continuous and discrete case. IEEE Trans. Fuzzy Syst. 8(5), 615–626 (2000)
Zhuang, X., Haralick, R.: Morphological structuring element decomposition. Computer Vis. Graph. Image Process. 35, 370–382 (1986)
Park, H., Chin, R.T.: Decomposition of arbitrarily shaped morphological structuring elements. IEEE Trans. Pattern Anal. Mach. Intell. 17(1), 2–15 (1995)
Author information
Authors and Affiliations
Corresponding author
Additional information
This work was financially supported by the GOA project B/04138/01 IV 1 of Ghent University and by CNPq under grant no. 306040/2006-9.
Rights and permissions
About this article
Cite this article
Mélange, T., Nachtegael, M., Sussner, P. et al. On the Decomposition of Interval-Valued Fuzzy Morphological Operators. J Math Imaging Vis 36, 270–290 (2010). https://doi.org/10.1007/s10851-009-0185-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10851-009-0185-7