Path-independent digital image correlation with high accuracy, speed and robustness

• Main Authors: Jiang, Zhenyu, Kemao, Qian, Miao, Hong, Yang, Jinglei, Tang, Liqun
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2016
• Subjects: Digital image correlation; Fast Fourier transform; Inverse compositional algorithm; Gauss–Newton method; Path-independence
• Online Access: https://hdl.handle.net/10356/81521; http://hdl.handle.net/10220/40826
• Institution: Nanyang Technological University

The initial guess transferring mechanism is widely used in iterative DIC algorithms and leads to path-dependence. Using the known deformation at a processed point to estimate the initial guess at its neighboring points could save considerable computation time, and a cogitatively-selected processing path contributes to the improved robustness. In this work, our experimental study demonstrates that a path-independent DIC method is capable to achieve high accuracy, efficiency and robustness in full-field measurement of deformation, by combining an inverse compositional Gauss–Newton (IC-GN) algorithm for sub-pixel registration with a fast Fourier transform-based cross correlation (FFT-CC) algorithm to estimate the initial guess. In the proposed DIC method, the determination of initial guess accelerated by well developed software library can be a negligible burden of computation. The path-independence also endows the DIC method with the ability to handle the images containing large discontinuity of deformation without manual intervention. Furthermore, the possible performance of the proposed path-independent DIC method on parallel computing device is estimated, which shows the feasibility of the development of real-time DIC with high-accuracy.