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Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow

Quantitative metallography to understand the morphology of different crystallographic phases in a material often rests on the segmentation and classification of electron backscatter diffraction (EBSD) maps. Image analysis offers rich toolboxes to perform such tasks based on ‘scalar’ images. Embracin...

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Detalles Bibliográficos
Autores principales: Mollens, Maxime, Roux, Stéphane, Hild, François, Guery, Adrien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9172027/
https://www.ncbi.nlm.nih.gov/pubmed/35719310
http://dx.doi.org/10.1107/S1600576722004265
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author Mollens, Maxime
Roux, Stéphane
Hild, François
Guery, Adrien
author_facet Mollens, Maxime
Roux, Stéphane
Hild, François
Guery, Adrien
author_sort Mollens, Maxime
collection PubMed
description Quantitative metallography to understand the morphology of different crystallographic phases in a material often rests on the segmentation and classification of electron backscatter diffraction (EBSD) maps. Image analysis offers rich toolboxes to perform such tasks based on ‘scalar’ images. Embracing the entire wealth of information provided by crystallography, operations such as erosion, dilation, interpolation, smoothing and segmentation require generalizations to do justice to the very nature of crystal orientations (e.g. preserving properties like frame indifference). The present study gives such extensions based on quaternion representation of crystal orientations. A dual-phase stainless steel specimen is used to illustrate the different steps of such a procedure.
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spelling pubmed-91720272022-06-17 Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow Mollens, Maxime Roux, Stéphane Hild, François Guery, Adrien J Appl Crystallogr Research Papers Quantitative metallography to understand the morphology of different crystallographic phases in a material often rests on the segmentation and classification of electron backscatter diffraction (EBSD) maps. Image analysis offers rich toolboxes to perform such tasks based on ‘scalar’ images. Embracing the entire wealth of information provided by crystallography, operations such as erosion, dilation, interpolation, smoothing and segmentation require generalizations to do justice to the very nature of crystal orientations (e.g. preserving properties like frame indifference). The present study gives such extensions based on quaternion representation of crystal orientations. A dual-phase stainless steel specimen is used to illustrate the different steps of such a procedure. International Union of Crystallography 2022-06-01 /pmc/articles/PMC9172027/ /pubmed/35719310 http://dx.doi.org/10.1107/S1600576722004265 Text en © Maxime Mollens et al. 2022 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
spellingShingle Research Papers
Mollens, Maxime
Roux, Stéphane
Hild, François
Guery, Adrien
Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow
title Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow
title_full Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow
title_fullStr Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow
title_full_unstemmed Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow
title_short Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow
title_sort insights into a dual-phase steel microstructure using ebsd and image-processing-based workflow
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9172027/
https://www.ncbi.nlm.nih.gov/pubmed/35719310
http://dx.doi.org/10.1107/S1600576722004265
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