Citation: 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
Academic Editor: Silvia Liberata Ullo
Received: 17 November 2022
Revised: 20 December 2022
Accepted: 26 December 2022
Published: 30 December 2022
Copyright: © 2022 by the authors.
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/).
Article
Automatic Method for Vickers Hardness Estimation by
Image Processing
Jonatan D. Polanco
1
, Carlos Jacanamejoy-Jamioy
1
, Claudia L. Mambuscay
1,2
and 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
* Correspondence: mgforero@yahoo.es
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 5
N
and 10
N
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
1. Introduction
The study of the properties of materials is of great importance to determine their
behavior in specific applications. Mechanical properties such as hardness, ductility, or
stiffness can be studied from laboratory tests to determine the appropriate characteristics
for their use. Hardness is one of the most important mechanical properties of materials, as it
allows for determining the resistance to deformation by a harder material [
1
,
2
]. There are
different hardness tests and these vary depending on the type of material, e.g., the Brinell
hardness test is best suited to determine the hardness of wood-based materials, or materials
with relatively low hardnesses [
3
]. On other hand, the Mohs hardness is the most commonly
used to identify minerals [4], Shore hardness implemented in polymeric materials [5] and
Vickers hardness to determine the hardness of metals, ceramics, and other materials. Studies
have shown that modifications can be made to Vickers hardness equipment to determine
other properties such as elasticity or surface stresses of the material [6,7].
Materials such as steel used in automotive axles, cutting tools, among other applica-
tions, are subjected to constant forces or loads, which can cause deformation or breakage
of the material. The search for continuous improvement has led to the implementation of
materials in the form of thin films, which consist of improving the surface properties of
the substrate such as steel, providing high hardness, low coefficient of friction, and wear
J. Imaging 2023, 9, 8. https://doi.org/10.3390/jimaging9010008 https://www.mdpi.com/journal/jimaging
