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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2013
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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. |
format | Online Article Text |
id | pubmed-3786070 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
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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