Laboratory for Dynamics of Machines and Structures 
Phase-based displacement identification in digital images for vibration measurement



Abstract
In recent years, phase-based methods for displacement identification in digital images have substantially gained in popularity. State of the art approaches to phase-based motion identification are already considered a valid alternative to gradient-based methods (e. g. optical flow) also in vibration measurement applications. Combined gradient and phase-based approaches aim to extract as much motion information from high-speed digital video as possible, improving the signal-to-noise-ratio of image-based measurements. The goal of this thesis is to survey the available tools for spatiotemporal phase calculation in digital images within the Python framework and implement a phase-based displacement identification algorithm, as well as assess the possibility of extending this algorithm into a phase-based motion magnification application.