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Fault detection by skeleton extraction based on orientation field consistency
A fault detection method using skeleton extraction based on orientation field consistency is proposed to improve the efficiency of fault detection, reduce the influence of transverse nonstructural factors on fault detection, and realize automatic fault extraction. In fingerprint image processing, th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286296/ https://www.ncbi.nlm.nih.gov/pubmed/35839234 http://dx.doi.org/10.1371/journal.pone.0271615 |
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author | Li, Yang Zhong, Baorong Xu, Xiaohong Liang, Zijun |
author_facet | Li, Yang Zhong, Baorong Xu, Xiaohong Liang, Zijun |
author_sort | Li, Yang |
collection | PubMed |
description | A fault detection method using skeleton extraction based on orientation field consistency is proposed to improve the efficiency of fault detection, reduce the influence of transverse nonstructural factors on fault detection, and realize automatic fault extraction. In fingerprint image processing, the consistency of the orientation field reaches a maximum value when all orientations are parallel and takes a smaller value when not all orientations are parallel. The orientation field ceases to be parallel in the presence of a stratigraphic discontinuity, and the consistency of the orientation field in the corresponding region is lower than that in parallel regions. This characteristic can be exploited to extract discontinuous regions from seismic data. Then, binarization and closing operations are used to extract fault areas and increase fault continuity. Finally, a skeleton extraction method based on extracting the longitudinal center point is used to identify the fault lines. Compared with the classical ant tracking method, the proposed method requires the adjustment of fewer parameters, thus simplifying fault identification process to a certain extent. Moreover, the proposed method effectively suppresses transverse discontinuities, highlights the longitudinal fault characteristics, and strengthens fault continuity. |
format | Online Article Text |
id | pubmed-9286296 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92862962022-07-16 Fault detection by skeleton extraction based on orientation field consistency Li, Yang Zhong, Baorong Xu, Xiaohong Liang, Zijun PLoS One Research Article A fault detection method using skeleton extraction based on orientation field consistency is proposed to improve the efficiency of fault detection, reduce the influence of transverse nonstructural factors on fault detection, and realize automatic fault extraction. In fingerprint image processing, the consistency of the orientation field reaches a maximum value when all orientations are parallel and takes a smaller value when not all orientations are parallel. The orientation field ceases to be parallel in the presence of a stratigraphic discontinuity, and the consistency of the orientation field in the corresponding region is lower than that in parallel regions. This characteristic can be exploited to extract discontinuous regions from seismic data. Then, binarization and closing operations are used to extract fault areas and increase fault continuity. Finally, a skeleton extraction method based on extracting the longitudinal center point is used to identify the fault lines. Compared with the classical ant tracking method, the proposed method requires the adjustment of fewer parameters, thus simplifying fault identification process to a certain extent. Moreover, the proposed method effectively suppresses transverse discontinuities, highlights the longitudinal fault characteristics, and strengthens fault continuity. Public Library of Science 2022-07-15 /pmc/articles/PMC9286296/ /pubmed/35839234 http://dx.doi.org/10.1371/journal.pone.0271615 Text en © 2022 Li et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Li, Yang Zhong, Baorong Xu, Xiaohong Liang, Zijun Fault detection by skeleton extraction based on orientation field consistency |
title | Fault detection by skeleton extraction based on orientation field consistency |
title_full | Fault detection by skeleton extraction based on orientation field consistency |
title_fullStr | Fault detection by skeleton extraction based on orientation field consistency |
title_full_unstemmed | Fault detection by skeleton extraction based on orientation field consistency |
title_short | Fault detection by skeleton extraction based on orientation field consistency |
title_sort | fault detection by skeleton extraction based on orientation field consistency |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286296/ https://www.ncbi.nlm.nih.gov/pubmed/35839234 http://dx.doi.org/10.1371/journal.pone.0271615 |
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