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Embedded Image Processing Systems for Automatic Recognition of Cracks using UAVs

机译:使用无人机自动识别裂缝的嵌入式图像处理系统

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Aiming at the use of Unmanned Aerial Vehicle (UAV) in civil construction for autonomous inspection of building pathologies, this paper discusses some implementation alternatives of image processing algorithms for the detection of cracks in building facades. These algorithms should run in an embedded computing platform installed on UAVs. Two image processing algorithms for crack detection and classification were selected and different embedded system implementations were evaluated. A version of the algorithms running in a Matlab environment on a desktop computer, which can be used in an approach on which the image processing is done in the ground and the UAV is only applied for image acquisition, was used as a baseline for the comparison. This baseline is compared with implementations running on an embedded processor (a Raspberry PI, running a distribution of Debian ARM operating system) and with implementations on a Xilinx FPGA-board installed in the UAV. Different scenarios for the execution of a inspection task of building facades were defined and the obtained results are presented in the paper.
机译:针对在民用建筑中对无人机进行建筑物病理自动检查的无人飞行器(UAV)的使用,本文讨论了用于检测建筑立面裂缝的图像处理算法的一些实现方案。这些算法应在安装在无人机上的嵌入式计算平台中运行。选择了两种用于裂纹检测和分类的图像处理算法,并评估了不同的嵌入式系统实现。在台式计算机上在Matlab环境中运行的算法的一种版本,可以作为比较的基准,该算法可用于在地面上进行图像处理并且仅将UAV应用于图像采集的方法。 。将该基准与在嵌入式处理器(Raspberry PI,运行Debian ARM操作系统的发行版)上运行的实现以及在无人机中安装的Xilinx FPGA板上的实现进行比较。定义了执行建筑物外墙检查任务的不同方案,并在本文中介绍了获得的结果。

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