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Analysing Arbitrary Curves from the Line Hough Transform

The Hough transform is commonly used for detecting linear features within an image. A line is mapped to a peak within parameter space corresponding to the parameters of the line. By analysing the shape of the peak, or peak locus, within parameter space, it is possible to also use the line Hough tran...

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Detalles Bibliográficos
Autores principales: Bailey, Donald, Chang, Yuan, Le Moan, Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321016/
https://www.ncbi.nlm.nih.gov/pubmed/34460728
http://dx.doi.org/10.3390/jimaging6040026
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author Bailey, Donald
Chang, Yuan
Le Moan, Steven
author_facet Bailey, Donald
Chang, Yuan
Le Moan, Steven
author_sort Bailey, Donald
collection PubMed
description The Hough transform is commonly used for detecting linear features within an image. A line is mapped to a peak within parameter space corresponding to the parameters of the line. By analysing the shape of the peak, or peak locus, within parameter space, it is possible to also use the line Hough transform to detect or analyse arbitrary (non-parametric) curves. It is shown that there is a one-to-one relationship between the curve in image space, and the peak locus in parameter space, enabling the complete curve to be reconstructed from its peak locus. In this paper, we determine the patterns of the peak locus for closed curves (including circles and ellipses), linear segments, inflection points, and corners. It is demonstrated that the curve shape can be simplified by ignoring parts of the peak locus. One such simplification is to derive the convex hull of shapes directly from the representation within the Hough transform. It is also demonstrated that the parameters of elliptical blobs can be measured directly from the Hough transform.
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spelling pubmed-83210162021-08-26 Analysing Arbitrary Curves from the Line Hough Transform Bailey, Donald Chang, Yuan Le Moan, Steven J Imaging Article The Hough transform is commonly used for detecting linear features within an image. A line is mapped to a peak within parameter space corresponding to the parameters of the line. By analysing the shape of the peak, or peak locus, within parameter space, it is possible to also use the line Hough transform to detect or analyse arbitrary (non-parametric) curves. It is shown that there is a one-to-one relationship between the curve in image space, and the peak locus in parameter space, enabling the complete curve to be reconstructed from its peak locus. In this paper, we determine the patterns of the peak locus for closed curves (including circles and ellipses), linear segments, inflection points, and corners. It is demonstrated that the curve shape can be simplified by ignoring parts of the peak locus. One such simplification is to derive the convex hull of shapes directly from the representation within the Hough transform. It is also demonstrated that the parameters of elliptical blobs can be measured directly from the Hough transform. MDPI 2020-04-23 /pmc/articles/PMC8321016/ /pubmed/34460728 http://dx.doi.org/10.3390/jimaging6040026 Text en © 2020 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Bailey, Donald
Chang, Yuan
Le Moan, Steven
Analysing Arbitrary Curves from the Line Hough Transform
title Analysing Arbitrary Curves from the Line Hough Transform
title_full Analysing Arbitrary Curves from the Line Hough Transform
title_fullStr Analysing Arbitrary Curves from the Line Hough Transform
title_full_unstemmed Analysing Arbitrary Curves from the Line Hough Transform
title_short Analysing Arbitrary Curves from the Line Hough Transform
title_sort analysing arbitrary curves from the line hough transform
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321016/
https://www.ncbi.nlm.nih.gov/pubmed/34460728
http://dx.doi.org/10.3390/jimaging6040026
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