Digital assisted image correlation for metal sheet strain measurement

Abstract

Current methods of correlation and point matching between stereoscopic images produce large errors or are completely inefficient when the surface has a repetitive, non-isotropic, low contrast pattern. In this article a new method of Digital Assisted Image Correlation (DAIC) is presented to match specific points in order to estimate the deformation of the surface in the metal sheets used in the automotive industry. To achieve this, it is necessary to stamp the surface to be measured with a regular pattern of points, then a digital image processing is done to obtain the labels of the circles of the pattern. After this, a semi-automatic search is made in the labels of both images to correlate all of them and perform the triangulation. DIC is used to corroborate the correspondence between points and verify the accuracy and efficiency of the developed method. This allows the 3D reconstruction of the sheet with a minimum of information and provides more efficiency and a great benefit in computational cost. Deformation is calculated by two methods, which show similarity between the values obtained with a digital microscope. It is assumed that quality of marks stamping, lighting, and the initial conditions, also contribute for trustworthy effects.