Algorithm for automatic detection and measurement of Vickers indentation hardness using image processing

Abstract

In this paper, we present a novel algorithm for the automatic detection and measurement of Vickers indentation hardness, using image processing. This algorithm uses image segmentation via binarization, automatically evaluating the mean and extreme gray values by means of standard histogram equalization so as to determine the optimal binarization threshold from each input image. We use a morphological filter and region growing to identify the indentation footprint. Our algorithm determines the four indentation vertices required to calculate diagonal lengths and Vickers hardness number. This algorithm is applied to 230 indentation images of steel-316 and hafnium nitride specimens, obtained using a micro hardness machine. The proposed algorithm can measure the Vickers hardness number of specimens using their indentation images. The algorithm results have a relative error of less than 3% with respect to those obtained through a conventional manual procedure. This algorithm can be used for indentation images with low contrast and irregular indentation edges.

An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation

“…The rapid development of high-resolution load/depth sensing technologies has inspired a tremendous interest in measuring the strain hardening properties of various materials by indentation experiments [ 4 , 5 ]. The main advantage of the indentation test is that the experiment process is very simple and versatile [ 5 , 6 , 7 ]. It can also be used for the in situ measurement of material properties in a very local region, where the conventional uniaxial experiment is not applicable [ 5 , 6 , 7 ].…”

“…The main advantage of the indentation test is that the experiment process is very simple and versatile [ 5 , 6 , 7 ]. It can also be used for the in situ measurement of material properties in a very local region, where the conventional uniaxial experiment is not applicable [ 5 , 6 , 7 ].…”

“…The use of the FE method makes it possible to build potential correlations between material constitutive parameters and the mechanical responses obtained from the indentation test. Based on this, considerable efforts have been made and many promising methods [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ] have been established to obtain the elastoplastic properties of material by indentation experiments. Among these previous works [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ], the indentation load-displacement curve has always been considered, and iterative optimization algorithms have been adopted to minimize the discrepancy between experiment and simulations [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ].…”

“…Based on this, considerable efforts have been made and many promising methods [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ] have been established to obtain the elastoplastic properties of material by indentation experiments. Among these previous works [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ], the indentation load-displacement curve has always been considered, and iterative optimization algorithms have been adopted to minimize the discrepancy between experiment and simulations [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. Numerical methods for measuring the elastoplastic properties of materials are essentially based on the deterministic optimization process, with extensive FE simulations using parameter iterative updating, e.g., the gradient-based optimization [ 6 , 11 ], and the Nelder–Mead search method [ 13 , 14 ].…”

“…Therefore, it is very necessary to consider the uncertainties in measuring the material parameters using indentation experiments and numerical algorithms. Moreover, in many indentation studies [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ], the load-displacement curve was mainly considered in numerical modeling in the parameter identification process. However, obtaining a unique solution is a challenge when only the indentation load-displacement curve is considered in the parameter identification process [ 2 , 9 , 11 , 12 ].…”