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Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils

This paper presents a new automatic framework for extracting and characterizing the dynamic shape of the 3D wetting front and its propagation, based in a sequence of tomographic images acquired as water (moisture) infiltrates in unsaturated soils. To the best of the authors’ knowledge, the shape of...

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Detalles Bibliográficos
Autores principales: Vasquez, Dionicio, Scharcanski, Jacob, Wong, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300084/
https://www.ncbi.nlm.nih.gov/pubmed/25602498
http://dx.doi.org/10.1371/journal.pone.0115218
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author Vasquez, Dionicio
Scharcanski, Jacob
Wong, Alexander
author_facet Vasquez, Dionicio
Scharcanski, Jacob
Wong, Alexander
author_sort Vasquez, Dionicio
collection PubMed
description This paper presents a new automatic framework for extracting and characterizing the dynamic shape of the 3D wetting front and its propagation, based in a sequence of tomographic images acquired as water (moisture) infiltrates in unsaturated soils. To the best of the authors’ knowledge, the shape of the 3D wetting front and its propagation and progress over time has not been previously produced as a whole by methods in existing literature. The proposed automatic framework is composed two important and integrated modules: i) extraction of the 3D wetting front, and ii) characterization and description of the 3D wetting front to obtain important information about infiltration process. The 3D wetting front surface is segmented from 3D CT imagery provided as input via a 3D stochastic region merging strategy using quadric-regressed bilateral space-scale representations. Based on the 3D segmentation results, the normal directions at local curvature maxima of the wetting front surface are computed for 3D images of soil moisture, and its propagation is analyzed at the local directions in sites of maximal water adsorption, and described using histograms of curvature changes over time in response to sample saturation. These curvature change descriptors provide indirect measurements of moisture infiltration in soils, and soil saturation. Results using a field tomograph equipment specific for soil studies are encouraging, and suggest that the proposed automatic framework can be applied to estimate the infiltration of water in soils in 3D and in time.
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spelling pubmed-43000842015-01-30 Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils Vasquez, Dionicio Scharcanski, Jacob Wong, Alexander PLoS One Research Article This paper presents a new automatic framework for extracting and characterizing the dynamic shape of the 3D wetting front and its propagation, based in a sequence of tomographic images acquired as water (moisture) infiltrates in unsaturated soils. To the best of the authors’ knowledge, the shape of the 3D wetting front and its propagation and progress over time has not been previously produced as a whole by methods in existing literature. The proposed automatic framework is composed two important and integrated modules: i) extraction of the 3D wetting front, and ii) characterization and description of the 3D wetting front to obtain important information about infiltration process. The 3D wetting front surface is segmented from 3D CT imagery provided as input via a 3D stochastic region merging strategy using quadric-regressed bilateral space-scale representations. Based on the 3D segmentation results, the normal directions at local curvature maxima of the wetting front surface are computed for 3D images of soil moisture, and its propagation is analyzed at the local directions in sites of maximal water adsorption, and described using histograms of curvature changes over time in response to sample saturation. These curvature change descriptors provide indirect measurements of moisture infiltration in soils, and soil saturation. Results using a field tomograph equipment specific for soil studies are encouraging, and suggest that the proposed automatic framework can be applied to estimate the infiltration of water in soils in 3D and in time. Public Library of Science 2015-01-20 /pmc/articles/PMC4300084/ /pubmed/25602498 http://dx.doi.org/10.1371/journal.pone.0115218 Text en © 2015 Vasquez et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Vasquez, Dionicio
Scharcanski, Jacob
Wong, Alexander
Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils
title Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils
title_full Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils
title_fullStr Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils
title_full_unstemmed Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils
title_short Automatic Framework for Extraction and Characterization of Wetting Front Propagation Using Tomographic Image Sequences of Water Infiltrated Soils
title_sort automatic framework for extraction and characterization of wetting front propagation using tomographic image sequences of water infiltrated soils
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300084/
https://www.ncbi.nlm.nih.gov/pubmed/25602498
http://dx.doi.org/10.1371/journal.pone.0115218
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