在低光照环境下，目前研究人员多采用LED标靶结合图像阈值方法来解决被测结构表面自然纹理可见度和分辨率下降，进而影响结构动挠度视觉测量精度的问题。但实际应用过程中，周围复杂的环境光线和不良天气均会对结构动挠度视觉测量结果的准确性造成影响。为此，本文提出了一种基于迭代Otsu法的桥梁结构动挠度视觉测量方法，该方法通过多次迭代求解光斑图像ROI区域前景阈值，配合光斑圆形度和帧间面积一致性约束，不断缩小灰度阈值范围，最终找到可有效分离图像前景光斑与背景的理想阈值，并结合灰度质心法准确计算出被测结构动挠度变化。本文首先介绍了基于迭代Otsu法的图像阈值分割原理和结构动挠度计算流程，之后通过一个悬臂梁试验，验证了所提出方法在有强光和雾气干扰的低光照环境下，仍能准确识别出结构动挠度。

Currently, researchers employ LED targets combining with image thresholding method to address the issue that the visibility and resolution of structural surface characteristics decrease due to the influence of low-light environment, and finally induce the worse performance for the structural dynamic parameters measurement when using the vision-based technology. However, on the other hand, the complex ambient lighting and unfavorable weather in practical application will inevitably induce the negative effect for the vision-based measurement of the structural parameters. Therefore, in order to deal with this issue, a novel vision-based measurement method was proposed in this paper based on the iterative Otsu algorithm, in which the correct segmentation of the foreground spot and background image with the influence of strong light and fog interference can be realized by iteratively solving the image foreground threshold when combining with the iterative constraints of spot roundness and inter-frame area consistency, and fianlly the structural dynamic deflection can be obtained after collecting the spot center by the gray centroid algorithm. In this paper, the principle of the image thresholding segmentation based on the proposed iterative Otsu algorithm and the corresponding procedure for the structural displacement measurement were introduced at first. Subsequently, a cantilever beam specimen was 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 with the influence of strong light and fog.

国家自然科学基金项目（面上项目，重点项目，重大项目）,中国地震局地震研究所和应急管理部国家自然灾害防治研究院基本科研业务费专项资助项目