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Automatic Method for Vickers Hardness Estimation by Image Processing
Hardness is one of the most important mechanical properties of materials, since it is used to estimate their quality and to determine their suitability for a particular application. One method of determining quality is the Vickers hardness test, in which the resistance to plastic deformation at the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863246/ https://www.ncbi.nlm.nih.gov/pubmed/36662106 http://dx.doi.org/10.3390/jimaging9010008 |
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author | Polanco, Jonatan D. Jacanamejoy-Jamioy, Carlos Mambuscay, Claudia L. Piamba, Jeferson F. Forero, Manuel G. |
author_facet | Polanco, Jonatan D. Jacanamejoy-Jamioy, Carlos Mambuscay, Claudia L. Piamba, Jeferson F. Forero, Manuel G. |
author_sort | Polanco, Jonatan D. |
collection | PubMed |
description | Hardness is one of the most important mechanical properties of materials, since it is used to estimate their quality and to determine their suitability for a particular application. One method of determining quality is the Vickers hardness test, in which the resistance to plastic deformation at the surface of the material is measured after applying force with an indenter. The hardness is measured from the sample image, which is a tedious, time-consuming, and prone to human error procedure. Therefore, in this work, a new automatic method based on image processing techniques is proposed, allowing for obtaining results quickly and more accurately even with high irregularities in the indentation mark. For the development and validation of the method, a set of microscopy images of samples indented with applied forces of [Formula: see text] and [Formula: see text] on AISI D2 steel with and without quenching, tempering heat treatment and samples coated with titanium niobium nitride (TiNbN) was used. The proposed method was implemented as a plugin of the ImageJ program, allowing for obtaining reproducible Vickers hardness results in an average time of [Formula: see text] seconds with an accuracy of [Formula: see text] and a maximum error of [Formula: see text] with respect to the values obtained manually, used as a golden standard. |
format | Online Article Text |
id | pubmed-9863246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98632462023-01-22 Automatic Method for Vickers Hardness Estimation by Image Processing Polanco, Jonatan D. Jacanamejoy-Jamioy, Carlos Mambuscay, Claudia L. Piamba, Jeferson F. Forero, Manuel G. J Imaging Article Hardness is one of the most important mechanical properties of materials, since it is used to estimate their quality and to determine their suitability for a particular application. One method of determining quality is the Vickers hardness test, in which the resistance to plastic deformation at the surface of the material is measured after applying force with an indenter. The hardness is measured from the sample image, which is a tedious, time-consuming, and prone to human error procedure. Therefore, in this work, a new automatic method based on image processing techniques is proposed, allowing for obtaining results quickly and more accurately even with high irregularities in the indentation mark. For the development and validation of the method, a set of microscopy images of samples indented with applied forces of [Formula: see text] and [Formula: see text] on AISI D2 steel with and without quenching, tempering heat treatment and samples coated with titanium niobium nitride (TiNbN) was used. The proposed method was implemented as a plugin of the ImageJ program, allowing for obtaining reproducible Vickers hardness results in an average time of [Formula: see text] seconds with an accuracy of [Formula: see text] and a maximum error of [Formula: see text] with respect to the values obtained manually, used as a golden standard. MDPI 2022-12-30 /pmc/articles/PMC9863246/ /pubmed/36662106 http://dx.doi.org/10.3390/jimaging9010008 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Polanco, Jonatan D. Jacanamejoy-Jamioy, Carlos Mambuscay, Claudia L. Piamba, Jeferson F. Forero, Manuel G. Automatic Method for Vickers Hardness Estimation by Image Processing |
title | Automatic Method for Vickers Hardness Estimation by Image Processing |
title_full | Automatic Method for Vickers Hardness Estimation by Image Processing |
title_fullStr | Automatic Method for Vickers Hardness Estimation by Image Processing |
title_full_unstemmed | Automatic Method for Vickers Hardness Estimation by Image Processing |
title_short | Automatic Method for Vickers Hardness Estimation by Image Processing |
title_sort | automatic method for vickers hardness estimation by image processing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863246/ https://www.ncbi.nlm.nih.gov/pubmed/36662106 http://dx.doi.org/10.3390/jimaging9010008 |
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