Abstract Digital image correlation (DIC) is a cornerstone technique for displacement measurement, offering transformative potential for structural health monitoring (SHM) applications due to its non-contact nature and cost-effectiveness. However, in practical applications, image jitter caused by extended monitoring distances and suboptimal optical conditions degrades accuracy. Given the significant relationships among pixel resolution, stability, and DIC measurement accuracy, this paper proposes a study to improve image stability using corner detection methods to improve the measurement accuracy of DIC technology. First, a camera captures multiple dynamic displacement images of slowly moving objects at different distances. Then, image stabilization technology is applied to the images for algorithmic processing, followed by DIC analysis. The results show that under normal acquisition conditions, the relative errors of DIC-analyzed data at different distances range from 3.8 % to 8.6 %, with displacement errors increasing with distance. In contrast, the relative errors of data processed with image stabilization technology range from 3.2 % to 6.0 %, demonstrating accuracy improvements of 4.2 % to 34.1 % (the improvement in accuracy increases with increasing test distance). This indicates that image stabilization technology can effectively improve the accuracy of DIC-based displacement measurement.
Yang et al. (2026) studied this question.