An accelerated and accurate process for the initial guess calculation in Digital Image Correlation algorithm

The Digital Image Correlation (DIC) is now an effective method for measuring displacement in engineering fields. DIC includes a coarse search scheme with pixel-size accuracy for finding an initial guess (IG) followed by an iteration procedure to successively find the accurate/true displacements. The closer IG to the true displacement values, the higher the likelihood of convergence and the more efficient the convergence of the subsequent Newton-Raphson (NR) iteration procedure. This study introduced and verified a novel fuzzy-logic based approximation scheme intending to provide more accurate IG values after the standard full-field IG search scheme. The results based on numerical experiments showed that the novel step of IG searching scheme provided considerably more accurate IG values and reduced the computational costs of finding IG values by up to 88.5% compared to the standard scheme. Furthermore, the overall computational costs including the subsequent NR iteration procedure were reduced by 31.5%, which is substantial. To further test and demonstrate the robustness, accuracy and effectiveness of the novel DIC procedure, a large number of numerical experiments using images simulating a wide range of rigid body motions (rotation, translation) and tensile testing conditions was utilized. The results had a 98.8% accuracy rate and a 99% precision rate. The DIC procedure provided therefore efficient and accurate displacement/deformation measurements in different types of loading conditions which are used for studying the mechanics of acrylic medical bone cements that are of interest in our research laboratory