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Optimized 3D Segmentation Algorithm for Shelly Sand Images

Leonti, A., Fonseca, J. ORCID: 0000-0002-7654-6005, Valova, I., Beemer, R., Cannistraro, D., Pilskaln, C., DeFlorio, D. and Kelly, G. (2020). Optimized 3D Segmentation Algorithm for Shelly Sand Images. Paper presented at the 6th World Congress on Electrical Engineering and Computer Systems and Science (EECSS'20), 13-15 Aug 2020, Virtual Conference.

Abstract

There is much to be gained from analysing and studying calcareous sediment, with applications ranging from the study of climate change, rock dating, and even building offshore oil rigs and wind farms. One way of performing this analysis is to obtain a µCT scan of the sediment, allowing scientists and engineers to automate much of their analysis using software. Many existing and prospective analysis techniques require handling individual grains. Thus, fast and effective segmentation is an essential first step for any such analysis. Segmentation is non-trivial; these scans hold a lot of information, exhibit ambiguous boundaries between objects, and many objects are hollow, making it even more difficult to apply traditional watershed segmentation. Addressing these issues, in this paper we propose an optimized 3D segmentation (O3DS) algorithm based on watersheds. We make use of branch recursion, partition the image by height prior to segmentation, artificially reducing the size of the largest connected objects. These and additional changes are extremely effective in optimizing performance; O3DS reduces the time to segment a 659x925x932 scan of sediment by 95.4% and produces better or comparable results when compared to similar implementation by our co-author.

Publication Type: Conference or Workshop Item (Paper)
Publisher Keywords: Recursion, Watershed segmentation, 3D imaging, Microtomography, Calcareous sand
Subjects: Q Science > QA Mathematics
T Technology > TA Engineering (General). Civil engineering (General)
Departments: School of Mathematics, Computer Science & Engineering > Engineering > Civil Engineering
Date Deposited: 05 Oct 2020 11:25
URI: https://openaccess.city.ac.uk/id/eprint/25002
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