Automated road pavement marking detection from high resolution aerial images based on multi-resolution image analysis and anisotropic Gaussian filtering
Automated road pavement marking detection from high resolution aerial images based on multi-resolution image analysis and anisotropic Gaussian filtering
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DOI：
10.1109/icsps.2010.5555636
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发表时间：
2010-07
期刊：
影响因子：
--
通讯作者：
Hang Jin;Yanming Feng
中科院分区：
文献类型：
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作者：
Hang Jin;Yanming Feng
从遥感图像中提取道路特征是摄影测量和遥感界三十多年来的一个长期研究课题。大部分的早期工作只集中在线性特征检测方法，限制性的假设图像分辨率和道路外观。高分辨率数字航空图像的广泛使用使得提取子道路特征（例如道路路面标记）成为可能。在本文中，我们将专注于道路车道标记的自动提取，这是需要各种基于车道的车辆应用，如，自主车辆导航，车道偏离警告。该方法包括三个阶段：i）从低分辨率图像中提取道路中心线，ii）在原始图像中检测路面，iii）在生成的路面上提取路面标记。在昆士兰州布鲁斯高速公路的航拍图像数据集上对所提出的方法进行了测试，结果证明了我们方法的有效性。
Road features extraction from remotely sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.