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Proceedings Paper

Brief survey of the relationships between finite random sets and morphology
Author(s): Robert M. Haralick; Su S. Chen; Xinhua Zhuang
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Paper Abstract

In order to be able to optimally design morphological shape extraction algorithms operating on binary digital images, there needs to be a probability theory for finite random sets and probability relations that show how the probability changes as a finite random set is propagated through a morphological operation. In this paper, we develop such a theory for finite random sets. We then demonstrate how to apply this theory for calculating the probability that a set S perturbed by min or max noise N and dilated or eroded by a structuring element K is a subset, superset, or hits a given set R. In some cases we obtain exact results and in some cases we obtain bounds for the desired probability.

Paper Details

Date Published: 30 June 1994
PDF: 6 pages
Proc. SPIE 2300, Image Algebra and Morphological Image Processing V, (30 June 1994); doi: 10.1117/12.179200
Show Author Affiliations
Robert M. Haralick, Univ. of Washington (United States)
Su S. Chen, Univ. of Washington (United States)
Xinhua Zhuang, Univ. of Missouri/Columbia (United States)


Published in SPIE Proceedings Vol. 2300:
Image Algebra and Morphological Image Processing V
Edward R. Dougherty; Paul D. Gader; Michel Schmitt, Editor(s)

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