Extending DIC Applicability to Challenging Contexts Using a Novel Reference Image Updating Approach

In the presence of significant target motion or speckle pattern variation, Digital Image Correlation (DIC) encounters challenges in maintaining continuous subset matching. To strengthen the performance of DIC in such occasions, a novel DIC analysis framework is proposed in this paper as Elimination Method. Different from current reference frame updating methods represented by incremental correlation, the proposed method is based on iteration formed by multiple DIC analyses. As a result, it divides the continuous tracking problem of the complete image set into multiple sub-problems of lower complexity. As demonstrations, two scenarios that are unfeasible with current DICs (direct or incremental algorithms) are analyzed: rotation structures with large axial movement and laser speckle DIC on vibration targets. The former induces large inter-frame subset displacements and the latter faces unpredictable variance of speckle distributions that both significantly interfere DIC measurement. With the proposed method, both cases are successfully analyzed and the errors of which are evaluated with benchmarks.