Accurate displacement measurement via a self-adaptive digital image correlation method based on a weighted ZNSSD criterion

Abstract

Digital image correlation (DIC) technique has been increasingly employed to implement surface deformation measurements in many engineering fields. Practically, it has been demonstrated that the choice of subset sizes exerts a strong influence on measurement results of DIC, especially when there exists locally larger deformation over the subsets involved. This paper proposes a novel subpixel registration algorithm with Gaussian windows to implicitly optimize the subset sizes by adjusting the shape of Gaussian windows in a self-adaptive fashion with the aid of a so-called weighted zero-normalized sum-of-squared difference correlation criterion. The feasibility and effectiveness of the self-adaptive algorithm are carefully verified through a set of well-designed synthetic speckle images, which indicates that the presented algorithm is able to greatly enhance the accuracy and precision of displacement measurements as compared with the traditional subpixel registration methods.