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Lookup NU author(s): Dr Chris Willcocks,
Professor Boguslaw ObaraORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by Springer London, 2019.
For re-use rights please refer to the publisher's terms and conditions.
© 2019, Springer-Verlag London Ltd., part of Springer Nature. In this paper, a new approach is proposed to extract an ordered sequence of curvilinear structures in images, capturing the largest and most influential paths first and then progressively extracting smaller paths until a prespecified size is reached. The results are demonstrated both quantitatively and qualitatively using synthetic and real-world images. The method is shown to outperform comparator methods for certain cases of noise, object class, and scale, while remaining fundamentally easier to use due to its low parameter requirement.
Author(s): Alharbi SS, Willcocks CG, Jackson PTG, Alhasson HF, Obara B
Publication type: Article
Publication status: Published
Journal: Signal, Image and Video Processing
Print publication date: 01/07/2019
Online publication date: 20/02/2019
Acceptance date: 24/01/2019
Date deposited: 04/05/2021
ISSN (print): 1863-1703
ISSN (electronic): 1863-1711
Publisher: Springer London
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