A global DIC algorithm for tracking rotating objects using image unwrapping and FFT analysis

Digital Image Correlation applied to rotating objects is a challenging task due to the extremely large displacements to be detected and to the rotation of the subsets during revolutions. For these reasons, conventional DIC algorithms are limited to about 7 degrees rotations before losing tracking capabilities. Nevertheless, a full 360 degrees rotation is to be tracked in practical scenarios, so that a new paradigm in optical tracking of rotating objects remains urgent. In this paper, a global DIC algorithm is proposed to overcome the limitations of conventional methods. A simple analytical representation of the roto-translation is proposed, and an optimization algorithm is developed to find the rotation angle and center to minimize the discrepancies between the reference and rotated image. The critical issue of the procedure is represented by the selection of a reliable first guess, which, due to the presence of several local minima and a really sharp global minimum, needs to be extremely accurate for the optimization to converge. To this extent, a robust procedure is proposed based on image unwrapping and spatial-FFT analysis of the unwrapped image to infer a reliable first guess to be fed to the subsequent final optimization process. The approach was validated through experimental analysis of a rotating PC fan.