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Assessment of the feasibility of detecting concrete cracks in images acquired by unmanned aerial vehicles

机译:评估在无人机图像中检测混凝土裂缝的可行性

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摘要

An 8-rotor unmanned aerial vehicle is used as a working platform. Its motion characteristics in a hovering state are obtained using a non-contact measurement instrument, which, along with the modulation transfer function of its airborne images, indicates the reliability of the airborne images of unmanned aerial vehicles in a hovering state. By installing a laser range finder on the cradle synchronized with the camera shutter to measure the object distance, the pixel resolution of the object distance is obtained. The airborne images are then processed using the MAMAS image processing toolbox, from which the pixels of concrete cracks are extracted. Compared to a static image and direct manual measurements, the airborne image of the unmanned aerial vehicle has higher precision, indicating its wide potential applications as an alternative of the conventional inspection methods of bridge inspection vehicle and working platforms.
机译:使用八旋翼无人机作为工作平台。使用非接触式测量仪器可以获得其在悬停状态下的运动特性,该非接触式测量仪器连同其机载图像的调制传递函数,可表明处于悬停状态的无人飞行器的机载图像的可靠性。通过在与相机快门同步的支架上安装激光测距仪以测量物距,可以获得物距的像素分辨率。然后使用MAMAS图像处理工具箱处理机载图像,从中提取混凝土裂缝的像素。与静态图像和直接手动测量相比,无人飞行器的机载图像具有更高的精度,这表明它具有广泛的潜在应用,可替代桥梁检查车辆和工作平台的常规检查方法。

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