Recent progress in digital image correlation

In this paper, we report the following important progress recently made in the basic theory and implementation of digital image correlation (DIC) for deformation and shape 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 local parameter, called the sum of squared subset intensity gradient, and an easy-to-compute yet effective global parameter, called mean intensity gradient, for quality assessment of the local speckle pattern within each subset and entire speckle pattern, respectively. 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 mostly 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 (PZNSSD) criterion with two additional unknown parameters, which elegantly unifies these correlation criteria for pattern matching. Finally, to overcome the limitation of the existing DIC techniques, 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 or shape of objects containing geometrical discontinuities and discontinuous deformation.