Abstract
Mathematical morphology is a well-known theory to process binary, grayscale or color images. In this paper, we introduce interval-valued fuzzy mathematical morphology as an extension of classical and fuzzy morphology. It originates from the observation that the pixel values of a grayscale image are not always certain, and models this uncertainty using interval-valued fuzzy set theory. In this way, we are able to incorporate the uncertainty regarding measured pixel values into the toolbox of morphological operators. We focus our attention on a morphological model whose underlying logical framework is based on the Lukasiewicz-operators. For this model we investigate and discuss general theoretical properties, some computational aspects, as well as its relation to fuzzy morphology and classical grayscale morphology.
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Nachtegael, M., Sussner, P., Mélange, T., Kerre, E.E. (2008). An Interval-Valued Fuzzy Morphological Model Based on Lukasiewicz-Operators. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_54
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DOI: https://doi.org/10.1007/978-3-540-88458-3_54
Publisher Name: Springer, Berlin, Heidelberg
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