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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Bibliographic Details
Published inJournal of mathematical imaging and vision Vol. 60; no. 7; pp. 1167 - 1179
Main Authors Chung, Yu-Min, Day, Sarah
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2018
Springer Nature B.V
Subjects
Applications of Mathematics
Binary alloys
Computer Science
Digital imaging
Homology
Image Processing and Computer Vision
Image segmentation
Mathematical Methods in Physics
Signal,Image and Speech Processing
Persistent homology
Thresholding
Firn
Binary alloy
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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.
ISSN:0924-9907
1573-7683
DOI:10.1007/s10851-018-0802-4