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Accurate extraction of cracks on the underside of concrete bridges

机译:准确提取混凝土桥梁底面的裂缝

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Crack detection is crucial for maintaining the structural health and safety of concrete bridges. Previous studies mainly focus on the detection of thick and conspicuous cracks on bridge deck using high resolution images. However, it's difficult to obtain accurate crack detection results on the underside of bridges due to the fainter and thinner appearance and lower contrast of cracks to their background. To overcome this problem, we propose a modified Beamlet Tree-based crack detection method which searches for possible edges by hierarchically constructing difference filters. The proposed method is evaluated with real crack images on the underside of bridges collected by an unmanned aerial vehicle (UAV). Compared with competitors, our proposed method achieves better performance in terms of accuracy and completeness.
机译:裂缝检测对于维持混凝土桥梁的结构健康和安全至关重要。以前的研究主要集中在使用高分辨率图像检测桥面板上厚而明显的裂缝。但是,由于桥的表面较薄,较薄,且与背景的对比度较低,因此很难在桥的下面获得准确的裂纹检测结果。为了克服这个问题,我们提出了一种改进的基于小波树的裂缝检测方法,该方法通过分层构造差分滤波器来搜索可能的边缘。在无人驾驶飞机(UAV)收集的桥梁底面上使用真实裂缝图像评估了所提出的方法。与竞争对手相比,我们提出的方法在准确性和完整性方面具有更好的性能。

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