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Proceedings Paper

A study of interval-valued fuzzy morphology based on the minimum-operator
Author(s): M. Nachtegael; P. Sussner; T. Mélange; E. E. Kerre
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Paper Abstract

Pixels of a grayscale image are classically associated with a single grayscale value. However, capturing grayscale images comes along with two kinds of uncertainty: numerical uncertainty (do we measure the actual value of the pixel or just an approximation?) and spatial uncertainty (does the measured pixel correspond to the actual spatial position or has it shifted?). Interval-valued fuzzy set theory provides a framework to model grayscale images of which the captured grayscale values are uncertain. This is realized by associating every pixel with a closed interval of possible grayscale values instead of with one single value. Based on this image model, a new corresponding morphological framework to process these images (e.g., using dilation and erosion) has been developed. In that way, we are not only able to model the uncertainty that is present during image capturing, but we are also able to process it such that the information regarding the uncertainty is never lost. In this paper, we study the interval-valued fuzzy morphological model based on the minimum-operator. Properties that are relevant in the context of image processing, as well as some interesting decomposition and construction properties, are discussed. This study gives an insight in the morphological model and will help researchers when they want to apply it in practice.

Paper Details

Date Published: 26 February 2010
PDF: 7 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75463H (26 February 2010); doi: 10.1117/12.855669
Show Author Affiliations
M. Nachtegael, Ghent Univ. (Belgium)
P. Sussner, Univ. of Campinas (Brazil)
T. Mélange, Ghent Univ. (Belgium)
E. E. Kerre, Ghent Univ. (Belgium)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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