Currently, researchers use LED targets in combination with the image thresholding method to address the issue of decreased visibility and resolution of structural surfaces in low-light environments. This approach ultimately leads to poorer performance when measuring structural dynamic parameters using vision-based technology. However, complex ambient lighting and unfavorable weather in practical applications will inevitably induce negative effects on the vision-based measurement of structural parameters. Therefore, in order to deal with this issue, a novel vision-based measurement method is proposed in this paper based on the iterative Otsu algorithm. In this method, the correct segmentation of the foreground spot and the background under strong light and fog interference can be realized by iteratively solving the image foreground threshold while combining with the iterative constraints of spot roundness and inter-frame area consistency, and finally the structural dynamic deflection can be obtained after the spot center is collected using the gray centroid algorithm. Firstly, this paper introduces the principle of image thresholding segmentation based on the proposed iterative Otsu algorithm, as well as the corresponding procedure for structural displacement measurement. Subsequently, a cantilever beam specimen is employed to validate the feasibility and effectiveness of the proposed method, and finally the results demonstrate that the proposed method can realize the accurate identification of the structural dynamic deflection under low-light conditions even when influenced by strong light and fog.