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A one-dimensional slope detection approach

This paper extends the scale-invariant edge detector to the one-dimensional slope. It can accurately detect the slope and estimate its parameters. The method has been verified with several mathematical functions, sample sizes, and noise levels. A contrast-invariant operator is proposed to suppress n...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaochun, Liu, Chuancai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3786070/
https://www.ncbi.nlm.nih.gov/pubmed/24083116
http://dx.doi.org/10.1186/2193-1801-2-474
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author Zhang, Xiaochun
Liu, Chuancai
author_facet Zhang, Xiaochun
Liu, Chuancai
author_sort Zhang, Xiaochun
collection PubMed
description This paper extends the scale-invariant edge detector to the one-dimensional slope. It can accurately detect the slope and estimate its parameters. The method has been verified with several mathematical functions, sample sizes, and noise levels. A contrast-invariant operator is proposed to suppress noise. The inter-sample localization and interpolation greatly improve the accuracy. The proposed slope detector is also suitable for real-world signals. In additional to above-mentioned, a threshold formula is developed for the first derivative slope detector, and the upper-bound of the filterable noise level is also explored.
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spelling pubmed-37860702013-09-30 A one-dimensional slope detection approach Zhang, Xiaochun Liu, Chuancai Springerplus Research This paper extends the scale-invariant edge detector to the one-dimensional slope. It can accurately detect the slope and estimate its parameters. The method has been verified with several mathematical functions, sample sizes, and noise levels. A contrast-invariant operator is proposed to suppress noise. The inter-sample localization and interpolation greatly improve the accuracy. The proposed slope detector is also suitable for real-world signals. In additional to above-mentioned, a threshold formula is developed for the first derivative slope detector, and the upper-bound of the filterable noise level is also explored. Springer International Publishing 2013-09-20 /pmc/articles/PMC3786070/ /pubmed/24083116 http://dx.doi.org/10.1186/2193-1801-2-474 Text en © Zhang and Liu; licensee Springer. 2013 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Zhang, Xiaochun
Liu, Chuancai
A one-dimensional slope detection approach
title A one-dimensional slope detection approach
title_full A one-dimensional slope detection approach
title_fullStr A one-dimensional slope detection approach
title_full_unstemmed A one-dimensional slope detection approach
title_short A one-dimensional slope detection approach
title_sort one-dimensional slope detection approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3786070/
https://www.ncbi.nlm.nih.gov/pubmed/24083116
http://dx.doi.org/10.1186/2193-1801-2-474
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