# New Four Points Initialization for Digital Image Correlation in Metal-Sheet Strain Measurements
## 1 Introduction  
The quality control of mechanical stamping is a need in modern industries. Engineers are always looking to improve the mechanical work optimization. Specifically, in the mechanical industry of metal-sheets manufacture, it is necessary to know their mechanical properties to use them in the most suitable way [1, 2]. In this industry, the material properties such as Young's modulus, Poisson's ratio, anisotropic plastic ratio parameters and others are required for improving the design and manufacture processes by finite element analyses. On the other hand, the most commonly used method for finding the material properties is a tensile test with a strain-gauge type extensometer. However, the results from the extensometer are not applicable to measure the strain at a local point and the onset of diffuse necking. In contrast, the Digital Image Correlation (DIC) method is a state-of-the-art technique that can be used for an accurate strain measurement of material properties [3]. DIC has become a very popular technique in mechanics, particularly for measurement materials deformation without contact. It is aneconomic and versatile method which also offers a big amount of experimental data [4]. As digital cameras technology constantly improves in terms of resolution, lenses and frames per second (FPS), this technique allows covering a wide range of scale in space and time. DIC in stereo systems even reach non-planar cases, very common in the industry, meaning the three-dimensional reconstruction and access to volumetric data about the material and structure behavior through time. Nonetheless, the use of DIC data to validate models in a quantitative way or to identify with precision several constitutive parameters, remains an open problem. One of the reasons for this is the complicate compromise between the measuring resolution and the large space for the measuring to be done. A second reason is the state of the frontiers. A third reason is that the measured displacements are not directly compared with common simulations. Of course, there are several efforts presenting promising results, as well as [5], a work analyzing the damage in a super pension aerostatic balloon (SPB) used by the Japanese Aerospace Exploration Agency (JAXA) during the insufflate prove. The expansion, when it is not uniform, generates a concentration of stress and makes the balloon explode. They proved a new method called the Simplified Digital Image Correlation Method (SiDIC), in a rubber balloon, to verify if the SPB could be measured. The SiDIC identified in a correct way the non-deformed region even though the deformation was not precise. Below, a brief historical background of DIC is given. An open code 3D-DIC Toolbox for MATLAB, the one implemented algorithm for multiple cameras, inspired by biomechanics, was reported in [6]. They were verified using the Multiple Digital Image Correlation Method (MultiDIC) and low-cost hardware. In [7], a quick method to correlate digital images (3D-DIC) was proposed to implement real-time measuring. Two improvements came up: the development of an efficient algorithm of the inverse composition of Gauss-Newton (IC-GN) with parallel computing to avoid redundant calculation, and an efficient IC-GN algorithm which was used to reach a speed of 10 frames/second with a resolution of 5000 points per frame. For validation, the displacement field of a four-point bending beam was determined by the real-time 3D-DIC. The experimental results were verified in traditional Chinese medicine. In the publication of [8], a procedure was developed to generate a sequence of intermediate synthetic images for a gradual following of the transformation of the pixel's subset between the two external configurations. An adequate distortion function of image was defined in the whole image through adopting an algorithm based in characteristics and followed by a scheme of interpolation based in non-uniform rational B-spline (NURBS).