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Article

Automatic Method for Vickers Hardness Estimation by Image Processing

by
Jonatan D. Polanco
1,
Carlos Jacanamejoy-Jamioy
1,
Claudia L. Mambuscay
1,2,
Jeferson F. Piamba
1,2 and
Manuel G. Forero
3,*
1
Semillero Lún, Grupo D+Tec, Faculty of Engineering, Universidad de Ibagué, Ibagué 730007, Colombia
2
Semillero NOVAMAT, Faculty of Natural Science and Mathematics, Universidad de Ibagué, Ibagué 730007, Colombia
3
Professional School of Systems Engineering, Faculty of Engineering, Architecture and Urban Planning, Universidad Señor de Sipán, Chiclayo 14000, Lambayeque, Peru
*
Author to whom correspondence should be addressed.
J. Imaging 2023, 9(1), 8; https://doi.org/10.3390/jimaging9010008
Submission received: 17 November 2022 / Revised: 20 December 2022 / Accepted: 26 December 2022 / Published: 30 December 2022
(This article belongs to the Topic Computer Vision and Image Processing)

Abstract

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 5N and 10N 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 2.05 seconds with an accuracy of 98.3% and a maximum error of 4.5% with respect to the values obtained manually, used as a golden standard.
Keywords: Vickers hardness; hardness estimation; image processing; steel heat treating; mechanics of materials Vickers hardness; hardness estimation; image processing; steel heat treating; mechanics of materials

Share and Cite

MDPI and ACS Style

Polanco, J.D.; Jacanamejoy-Jamioy, C.; Mambuscay, C.L.; Piamba, J.F.; Forero, M.G. Automatic Method for Vickers Hardness Estimation by Image Processing. J. Imaging 2023, 9, 8. https://doi.org/10.3390/jimaging9010008

AMA Style

Polanco JD, Jacanamejoy-Jamioy C, Mambuscay CL, Piamba JF, Forero MG. Automatic Method for Vickers Hardness Estimation by Image Processing. Journal of Imaging. 2023; 9(1):8. https://doi.org/10.3390/jimaging9010008

Chicago/Turabian Style

Polanco, Jonatan D., Carlos Jacanamejoy-Jamioy, Claudia L. Mambuscay, Jeferson F. Piamba, and Manuel G. Forero. 2023. "Automatic Method for Vickers Hardness Estimation by Image Processing" Journal of Imaging 9, no. 1: 8. https://doi.org/10.3390/jimaging9010008

APA Style

Polanco, J. D., Jacanamejoy-Jamioy, C., Mambuscay, C. L., Piamba, J. F., & Forero, M. G. (2023). Automatic Method for Vickers Hardness Estimation by Image Processing. Journal of Imaging, 9(1), 8. https://doi.org/10.3390/jimaging9010008

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