Unstable video phase vibration measurement based on digital image stabilization

The technology for non-contact vibration measurement using video recorded by cameras has rapidly developed in recent years, however, existing methods are unable to effectively handle unstable video sources. This paper proposes a phase vibration measurement algorithm based on digital image stabilization, which employs the Kanade–Lucas–Tomasi feature tracking method to track feature points in the input video and derive affine transformation matrices between adjacent frames. Additionally, it utilizes the random sample consensus algorithm to eliminate outliers and smooth motion trajectories, applies the Hilbert transform to extract the global phase information of the stabilized video, uses the amplitude information to weight the phase information, and designs an adaptive filter to remove noise. Numerical simulations and experiments demonstrate the effectiveness and accuracy of the proposed method.