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Topological Fidelity and Image Thresholding: A Persistent Homology Approach
We develop a method based on persistent homology to analyze topological structure in noisy digital images. The method returns threshold(s) for image segmentation to represent inherent topological structure as well as estimates of topological quantities in the form of Betti numbers . Two motivating d...
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Published in: | Journal of mathematical imaging and vision 2018-09, Vol.60 (7), p.1167-1179 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We develop a method based on
persistent homology
to analyze topological structure in noisy digital images. The method returns threshold(s) for image segmentation to represent inherent topological structure as well as estimates of topological quantities in the form of
Betti numbers
. Two motivating data sets are scans of binary alloys and
firn
, the intermediate stage between snow and ice. |
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ISSN: | 0924-9907 1573-7683 |
DOI: | 10.1007/s10851-018-0802-4 |