Hyperspectral Imaging for Autonomous Inspection of Road Pavement Defects
Hyperspectral Imaging for Autonomous Inspection of Road Pavement Defects
复制标题
DOI：
10.22260/isarc2019/0052
复制
发表时间：
2019-05
期刊：
影响因子：
--
通讯作者：
M. Abdellatif;H. Peel;A. Cohn;R. Fuentes
中科院分区：
文献类型：
--
作者：
M. Abdellatif;H. Peel;A. Cohn;R. Fuentes
为了提高道路维修和保养的效率，道路的自主检查越来越受到人们的关注。在本文中，我们将展示使用高光谱相机 (HSC) 识别道路缺陷的潜力。本文的核心思想是，道路裂缝显示了路面内部材料，由于表面磨损，其化学成分与表面材料不同。路面的材料变化会产生光谱特征，可以在 HSC 图像中轻松检测到。这种情况有利于裂缝和坑洼的检测，如果仅在可见光谱域中工作，这可能会很困难。我们报告了使用 HSC 进行的实验，以确定道路材料的变化及其与裂缝和坑洼的关联。设计了一种新的指标来测量金属氧化物的数量，并将其缺失与裂纹的出现联系起来。该指标比文献中以前的指标更具辨别力。
Autonomous inspection of roads is gaining interest to improve the efficiency of road repair and maintenance. In this paper we will be showing the potential for using Hyper Spectral Cameras, HSC, to identify road defects. The key idea of this paper is that cracks in the road show the interior material of road pavement which have different chemical composition from the surface materials due to surface wear. Material changes of the road surface give rise to a spectral signature that can be easily detected in HSC images. This condition facilitates the detection of cracks and potholes, which can be difficult if working in the visible spectrum domain only. We report on experiments with a HSC to identify the road material changes and their association to cracks and potholes. A new metric is devised to measure the amount of metal oxides and associate its absence to the appearance of cracks. The metric is shown to be more discriminative than previous indicators in the literature.