Abstract
This paper shows how the Discrete Mereotopology notions of adjacency and neighbourhood between regions can be exploited through Mathematical Morphology to accept or reject changes resulting from traditional morphological operations such as closing and opening. This leads to a set of six morphological operations (here referred to generically as minimal opening and minimal closing)where minimal changes fulfil specific spatial constraints. We also present an algorithm to compute the RCC5D and RCC8D relation sets across multiple regions resulting in a performance improvement of over three orders of magnitude over our previously published algorithm for Discrete Mereotopology.
Original language | English |
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Pages (from-to) | 109-117 |
Number of pages | 9 |
Journal | Signal Processing: Image Communication |
Volume | 76 |
Early online date | 27 Apr 2019 |
DOIs | |
Publication status | Published - Aug 2019 |
Bibliographical note
Funding Information:The research reported in this paper was supported by the Engineering and Physical Sciences Research Council (EPSRC) , UK through funding under grant EP/M023869/1 ‘Novel context-based segmentation algorithms for intelligent microscopy’.
Keywords
- Discrete mereotopology
- Image processing
- Mathematical morphology
- Spatial reasoning