基于模板匹配和距离变换的半自动道路跟踪

Xiangguo Lin, Jixian Zhang, Zhengjun Liu, Jing Shen
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引用次数: 31

摘要

为了加快地理数据的获取和更新,迫切需要道路网的半自动提取。然而,在城市高分辨率遥感图像上,路面受到车辆遮挡或阴影的严重干扰,这使得大多数使用最小二乘模板匹配的道路跟踪器效率低下。幸运的是,许多令人不安的特征,如车辆、斑马、车道标记的规模比城市地区的带状路面要小。事实上,如果首先对灰度值的差异进行粗模板匹配,则欧氏距离变换可以扩大纯路面,侵蚀小的干扰特征。因此,欧几里得距离变换使模板匹配在城市道路网络跟踪中具有更强的鲁棒性。提出了一种基于模板匹配和欧氏距离变换的城市带状道路半自动提取方法。使用QuickBird图像在泰安地区的一个场景进行测试。结果表明,改进后的方法能够可靠、鲁棒地提取城市道路网。本文的主要贡献在于有力地证明了除最小二乘法之外的距离变换方法可以用于模板匹配来跟踪复杂的道路网。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semi-automatic road tracking by template matching and distance transform
Semi-automatic extraction of road networks is greatly needed to accelerate the acquisition and update of geodata. However, the road surfaces are seriously disturbed by occlusion of vehicles or shadows on high resolution remotely sensed imagery in urban areas, which makes most of road trackers, using least-squares template matching, inefficient. Fortunately, the scale of many disturbing features such as vehicles, zebras, lane markings is smaller than one of ribbon road surfaces in urban areas. As a matter of fact, Euclidean distance transform can dilate the pure road surface and erode the small disturbing features if a coarsely template matching by thresholding the differences of gray values is firstly performed. Consequently, the Euclidean distance transformation makes the template matching more robust in tracking road networks in urban areas. In this paper, a novel semi-automatic scheme based on template matching and Euclidean distance transformation is presented to extract ribbon roads in urban areas. A scene of QuickBird image over Tai'an area was used for test. The results show our improved method can reliably and robustly extract road networks in urban areas. The main contribution of this paper is that the method of distance transformation besides least squares can be used in template matching to track road networks with much complexity has been strongly proved.
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