A Lightweight DFT-Based Approach to the Optical Measurement of Displacements Using an Open-Source Python Code

Commonly available digital image correlation (DIC) tools are designed to evaluate displacement/deformation fields using well-optimized correlation functions and computational procedures. However, real-time monitoring at high sampling rates or tracking motion at predefined locations from large sequence images can be hardly accomplished due to extreme computational costs. As shown in this paper, a lightweight approach based on the registration of subpixel subset shifts using discrete Fourier transform (DFT) can easily tackle large sets of images if the measurement is limited to discrete locations. A simple open-source python software designed for evaluation of displacements using virtual extensometers is described in this paper, along with the analysis of its performance. It is shown that the DFT-based algorithms outperform a commonly used DIC package in terms of computational efficiency and required user interactions, without sacrificing precision and accuracy.