Generalized spatial-gradient-based digital image correlation for displacement and shape measurement with subpixel accuracy

Abstract

A generalized spatial-gradient-based digital image correlation (DIC) method is proposed for subpixel-accuracy displacement and shape measurement. The proposed method overcomes the limitations in existing spatial-gradient-based DIC methods by adopting a generalized linear intensity-change model, which can cope well with linear variation in lighting illumination and greyscale intensity change of an object's surface during the measurement. In addition, various displacement mapping functions can be easily incorporated into the proposed intensity-change model to approximate the underlying deformation of the subset, and a simple iterative least-squares algorithm is employed to detect the desired displacement parameters with a robust noise-proof performance. To evaluate the performance of the proposed technique, both computer simulation and an actual experiment have been carried out. The results clearly demonstrate that the proposed method can accurately measure the shape and displacement field, even when substantial intensity variations exist in the experimental images.