# New Four Points Initialization for Digital Image Correlation in Metal-Sheet Strain Measurements
## 1 Introduction
This allowed a fast and trustworthy estimation of the initial deformation parameters for the refinement phase after the DIC analysis, and tests were made on aluminum plates. Document [9] proposed a method of deconvolution to recover the real fields of displacement and tension of their counterparts provided by local DIC. The proposed algorithm could be considered an extension of the Van Cittert deconvolution, based on the small tension assumption. The authors claimed an improvement on the fine details in displacement and tension maps, as well as in space resolution. The guidelines to evaluate the precision and resolution of the 2D analysis under the patronage of the Society of Experimental Mechanics were reported in [10]. On the other hand, algorithms to map relative displacements of the deformed material points in opposition to non-deformed material by using DIC were reported in [11; 12]. The current possibilities for the DIC scale allows the study of deformation on different levels, from meters to the nanoscale [13; 14], with the condition of recording it correctly, following a known pattern like a circle grid or square grid. Additionally, studies have looked at how different systems behave, like biological materials [15; 16; 17; 18], metallic alloys [19; 20; 21], memory-shape alloys [22; 23], porous metals [24; 25; 26], polymers [27] and polymeric foams [28]. A key step in the process of DIC image tracking is the definition of the initial assumption, for the non-linear optimization routine aimed at finding the parameters that describe the transformation of the subset of pixels. This initialization can be very challenging and possibly fail when it comes to pairs of highly deformed images, such as those obtained from two angled views of non-planar objects. For example, in Figure 1, it can be seen how the global DIC cannot exactly match the circle mark to measure the strain. This was performed with the MATLAB function called \"imregcorr\", which was reported in [29]. As can be observed from the preceding discussion, there still is the question of whether it is possible to improve the DIC accurateness. In brief, these previous works highlight the need for developing a systematic approach for achieving this goal, which to the author's awareness has not yet been stated. Therefore, in this paper we propose the use of a mark-search as an initial condition and of DIC as the system to verify the point-pairing. We propose the use of a mark-search as an initial condition and the use of DIC as the system to verify the point-pairing, because the number of mechanical part images are plentiful, the search for features to measure is very broad, as a result of which providing the initial conditions is necessary to fully automate the process gradually. The lack of a correct initial condition generates slowness and inaccurateness in current implementations of DIC. An appropriate initial condition is especially useful to know the material properties, specifically, its deformation curve and characterization zones such as: elastic, inelastic and rupture [30]. The proposed method in this work is applied to galvanized steel sheet, used in the outside bodywork of a pickup truck at 620 \(\upmu\)m-thick and 96.5 \(\upmu\) hardness. Figure 2 shows the surface view of the material obtained from a metallographic microscope model:AX @ 200X, Company: Carl Zeiss AG, Jena, Turinga, Germany. It is necessary to mention that the experiments presented in this paper were all made for the automotive industry sector.