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Abstract Existing three-dimensional digital image correlation (3D-DIC) for surface 3D shape and deformation measurement requires the users to input key calculation parameters (e.g. subset size) to proceed with stereo and temporal matching. However, the lack of clear guidelines for optimal parameter selection often leads to ambiguity and uncertainty in the final measurements. To eliminate the ambiguity and realize full-automatic, user-independent, accurate and precise 3D-DIC measurements, we present a simple yet effective Smart DIC-3D. By fully considering local speckle quality and deformation, Smart DIC-3D automatically selects the optimal subset size for each calculation point in both stereo and temporal matching. Additionally, a fully automated initial value estimation method, combining speeded-up robust features with a reliability-guided displacement tracking strategy, ensures automatic reliable initial value estimation for both matching processes. Both numerical experiments with simulated stereo speckle images and practical applications including complex shape reconstruction and non-uniform deformation measurement were conducted to verify the effectiveness and accuracy of Smart DIC-3D. The experimental results show that Smart DIC-3D has lower random and under-matched systematic errors than regular 3D-DIC, enabling high-fidelity 3D shape reconstruction and deformation measurement independent of the practitioners’ input.
Pan et al. (Thu,) studied this question.