Measurement of large, discontinuous displacement from digital images

Abstract

One main limitation of conventional digital image correlation (DIC) methods is their incapacity to treat with large, discontinuous displacements. This paper seeks to resolve this issue using a variational method. Specifically, the objective function is written in a form of L1‐norm instead of L2‐norm for discontinuity preservation. This convex, non‐differentiable objective function is resolved by a proximal gradient method. Then, the entire correlation process is embedded into a multi‐level image pyramid, enabling large displacements to be measured accurately. The proposed method is first validated on images with prescribed small displacements; its performance to treat with discontinuous, large displacements is then examined. The results show that the proposed method exhibits an acceptable performance when measuring some extreme displacements up to 16.5 pixels in a 500 × 500 pixels resolution image. Concerning subpixel accuracy, the errors can be lessened to a very low level with optimised parameters even for a dense correlation at each pixel. Good performance is also demonstrated in forms of noise proof and illumination fluctuation tolerance. Finally, an application is conducted on an experiment concerned with cracking in desiccated soils, in which the proposed method succeeds in tracking the nucleation and propagation processes of multiple cracks.

Investigating the Effect of Water Saturation on Rock Fracture Characteristics: Some Insights from Digital Image Correlation Technology

“…Discontinuity issues in the DIC calculation have challenged the analysis of rock failure processes. Discontinuous significant displacement problems can be addressed through algorithm modifications, enabling the quantification of crack propagation . Additionally, experimental results have shown that the roughness of fracture surfaces exhibits certain characteristic scaling properties. , It provides insights into using the DIC method to extract fracture surface morphology and calculate fracture roughness.…”