Recent Progress in Digital Image Correlation

Abstract

In this paper, we report the following important progress recently made in the basic theory and practical implementation of digital image correlation (DIC) for deformation measurement. First, we answer a basic but confusing question to the users of DIC: what is a good speckle pattern for DIC? We present a simple, easy-to-compute yet effective global parameter, called mean intensity gradient, for quality assessment of the entire speckle pattern. Second, we provide an overview of various correlation criteria used in DIC for evaluating the similarity of the reference and deformed subsets, and demonstrate the equivalence of three robust and most widely used correlation criteria, i.e., a zero-mean normalized cross-correlation (ZNCC) criterion, a zero-mean normalized sum of squared difference (ZNSSD) criterion and a parametric zero-mean normalized sum of squared difference (PSSD_ab) criterion with two additional unknown parameters, which elegantly unifies these correlation criteria for subset-based pattern matching. Third, we describe an iterative least squares (ILS) algorithm for accurate subpixel motion detection, which is proved to be equivalent to the existing Newton–Raphson algorithm, but the principle and implementation of ILS algorithm is more straightforward and easier. Finally, to overcome the two limitations of existing subset-based DIC technique, we introduce a robust and generally applicable reliability-guided DIC technique, in which the calculation path is guided by the ZNCC coefficients of computed points, to determine the genuine full-field deformation of an object with complex shape.