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Research on 3D crack segmentation of CT images of oil rock core
In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image ba...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8516274/ https://www.ncbi.nlm.nih.gov/pubmed/34648545 http://dx.doi.org/10.1371/journal.pone.0258463 |
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author | Zou, Yongning Yao, Gongjie Wang, Jue |
author_facet | Zou, Yongning Yao, Gongjie Wang, Jue |
author_sort | Zou, Yongning |
collection | PubMed |
description | In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results. |
format | Online Article Text |
id | pubmed-8516274 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85162742021-10-15 Research on 3D crack segmentation of CT images of oil rock core Zou, Yongning Yao, Gongjie Wang, Jue PLoS One Research Article In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results. Public Library of Science 2021-10-14 /pmc/articles/PMC8516274/ /pubmed/34648545 http://dx.doi.org/10.1371/journal.pone.0258463 Text en © 2021 Zou 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 Zou, Yongning Yao, Gongjie Wang, Jue Research on 3D crack segmentation of CT images of oil rock core |
title | Research on 3D crack segmentation of CT images of oil rock core |
title_full | Research on 3D crack segmentation of CT images of oil rock core |
title_fullStr | Research on 3D crack segmentation of CT images of oil rock core |
title_full_unstemmed | Research on 3D crack segmentation of CT images of oil rock core |
title_short | Research on 3D crack segmentation of CT images of oil rock core |
title_sort | research on 3d crack segmentation of ct images of oil rock core |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8516274/ https://www.ncbi.nlm.nih.gov/pubmed/34648545 http://dx.doi.org/10.1371/journal.pone.0258463 |
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