Detecting roads from high-resolution aerial images: a position iteration algorithm for linear target detection

Hao He, Shuyang Wang, Qi Yang, Xu Huang, Qian Zhao
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Abstract

Detecting roads from high-resolution photographs can serve forestry, agriculture, traffic and even military areas, and produce significant social and economic value. In this paper, we present a novel method that utilizes the flatness and the connectivity to detect the road in high-resolution aerial images. The method iterates the probable locations of the roads by using the flatness and connects the roads by using the connectivity. Firstly, we introduce a concept of ‘footprint’, which reveals the probable location and extension direction of a road. Given an initial footprint, we assess the flatness between locations to search the resulting footprint. By iterating and connecting the footprints, our approach produces a set of connected line segments that reflect the road to be detected. In addition, a footprints initialization algorithm is introduced to make our method totally automatic, and a road network pruning algorithm is designed to make the result clearer and more accurate. Tested under three high-resolution aerial photographs, our method achieved an accuracy of more than 80%. The algorithm is adapted for road detection and still linear target detection in high-resolution aerial photographs. Since the algorithm does not require artificial features or training data, it can be quickly deployed in application.
高分辨率航拍图像道路检测:一种线性目标检测的位置迭代算法
从高分辨率照片中检测道路可以服务于林业、农业、交通甚至军事领域,并产生重大的社会和经济价值。在本文中,我们提出了一种利用平面度和连通性来检测高分辨率航空图像中的道路的新方法。该方法利用平整度迭代道路的可能位置,并利用连通性将道路连接起来。首先,我们引入了“足迹”的概念,它揭示了道路可能的位置和延伸方向。给定初始足迹,我们评估位置之间的平坦度以搜索结果足迹。通过迭代和连接足迹,我们的方法产生一组连接的线段,这些线段反映了要检测的道路。此外,引入了足迹初始化算法,使方法完全自动化;设计了路网剪枝算法,使结果更清晰、更准确。在三张高分辨率航空照片下进行测试,我们的方法达到了80%以上的精度。该算法适用于高分辨率航拍图像的道路检测和静止线性目标检测。由于该算法不需要人工特征或训练数据,因此可以快速部署到应用中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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