Bellas Acosta, I. and Stell, J.G. orcid.org/0000-0001-9644-1908 (2024) Monotone Ω-Sup-Fuzzy Relations: Converse and Complementation. In: Fahrenberg, U., Fussner, W. and Glück, R., (eds.) Relational and Algebraic Methods in Computer Science. 21st International Conference, RAMiCS 2024, 19-22 Aug 2024, Prague, Czechia. Lecture Notes in Computer Science, 14787 . Springer Nature , pp. 65-82. ISBN 978-3-031-68279-7
Abstract
L-fuzzy relations on a set X are functions from X x X to the lattice L and act on the L-fuzzy subsets of X. When L is the lattice of sup-preserving endomaps on a complete lattice Ω, the relations act also on the Ω-fuzzy subsets of X. We call these relations equipped with this action, Ω-sup-fuzzy relations. When X is a preorder, monotone relations of this form act on the lattice of monotone functions from X to Ω. The motivation comes from mathematical morphology in image processing. Grey-scale images are modelled as functions on sets of pixels with Ω as the set of grey levels. More generally, graphs and hypergraphs labelled by grey levels can be handled. Enriching the lattice of Ω-sup-fuzzy relations with a multiplication operation provides a unital quantale that acts on the lattice of grey-scale images via the morphological operations of dilation and erosion. We study the quantale of Ω-sup-fuzzy relations, with particular attention to the concepts of converse and complementation for these relations.
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Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2024. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-68279-7 |
Keywords: | Fuzzy relations; Quantales; Sup-preserving endomorphisms |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Jul 2024 13:13 |
Last Modified: | 14 Aug 2024 14:28 |
Status: | Published |
Publisher: | Springer Nature |
Series Name: | Lecture Notes in Computer Science |
Identification Number: | 10.1007/978-3-031-68279-7_5 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:214318 |
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