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An Automatic Pavement Surface Distress Inspection System

机译:自动路面破损检测系统

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摘要

This paper presents a customized image-processing algorithm for the high-speed and realtime detection of pavement surface distresses. The algorithm was developed based on the "grid cell" analysis, in which a pavement image is divided into a grid of 8 × 8 pixel cells, and each cell is classified as a non-crack cell or a crack cell based on the statistics of the grayscales of the cell pixels. A crack cell can be regarded as a seed for crack formation. Adjacent crack seeds or seed clusters are connected to a crack segment. Each segment has it own direction and contrast traced from all seed in the path. A full crack is a connection of nearby segments with similar directions and contrasts. Most importantly, there must be a clear crack path along these segments. Because many operations are performed on the grid cells rather than on the original image, the algorithm can detect the cracks in the current image during the time when the camera is capturing a new image. Therefore, the survey can run at real time at a highway speed. The' trial test results showed a good repeatability and accuracy when the system conducts multiple surveys and runs at different speeds and different weather conditions.
机译:本文提出了一种定制的图像处理算法,用于高速,实时地检测路面的破损情况。该算法是在“网格单元”分析的基础上开发的,其中,将路面图像划分为8×8像素单元的网格,并且根据像素的统计信息将每个单元分为非裂纹单元或裂纹单元。单元像素的灰度。裂纹单元可以视为裂纹形成的种子。相邻的裂纹种子或种子簇连接到裂纹段。每个片段都有其自己的方向和对比度,该对比度和对比度从路径中的所有种子开始追踪。完全裂缝是指具有相似方向和对比度的附近片段之间的连接。最重要的是,这些段上必须有一条清晰的裂纹路径。由于对网格单元而不是原始图像执行了许多操作,因此该算法可以在相机捕获新图像的过程中检测当前图像中的裂缝。因此,该调查可以实时以高速公路速度运行。当系统进行多次调查并以不同的速度和不同的天气条件运行时,试验结果显示出良好的可重复性和准确性。

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