| 利用可变形部件模型检测遥感影像道路交叉口 |
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| 引用本文： | 曹闻,李润生.利用可变形部件模型检测遥感影像道路交叉口[J].武汉大学学报(信息科学版),2018,43(3):413-419. |
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| 作者姓名： | 曹闻 李润生 |
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| 作者单位： | 1.信息工程大学地理空间信息学院, 河南 郑州, 450001 |
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| 摘 要： | 为了解决高分辨率遥感影像道路交叉口位置检测与类型识别问题，提出了一种基于可变形部件模型的道路交叉口检测方法。首先，分析了道路交叉口在高分辨率遥感影像上的表征形式；然后，借鉴面向对象的思想，利用可变形部件模型，通过训练和学习其整体和部件组成的空间布局特征获取目标对象模型参数；最后，通过滑动窗口搜索匹配方法获取道路交叉口位置和其对应的类型。由仿真与实验结果可知，此算法不仅能够自动、准确地检测道路交叉口的几何位置，而且能够识别其几何形状类型，可有效提高道路网络拓扑结构构建效率。
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| 关 键 词： | 高分辨率遥感影像 道路交叉口 可变形部件模型 HOG特征 |
| 收稿时间： | 2016-03-06 |
Road Intersections Detection Using Deformable Part Models on Remote Sensing Image |
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| Institution: | 1.Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China2.School of Navigation and Aerospace Engineering, Information Engineering University, Zhengzhou 450001, China |
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| Abstract: | With the rapid development of high-resolution remote sensors, how to rapidly, automatically and accurately extract road intersections using high-resolution remote sensing images has become a focus which draws attention in the academic field and several management departments. The current methods of road networks extraction can be divided into two types. The first kind method is to construct road networks according as road intersections computation on the basis of road extraction, but it exists the defect and deficiency of full automatic and suitability. The second kind method is to construct road networks according as road extraction on the basis of road intersections extraction, but it is almost appropriated for low-resolution remote sensing image. Therefore, in order to solve the problem of geometric position detection and geometric shape type identification of road intersections in high-resolution remote sensing images, this paper proposes a road intersections detecting method based on the deformable part models:Firstly, the image features of road intersections are studied in high-resolution remote sensing image; Secondly, road intersection is regarded as a object which is made up of root and many parts, meanwhile, the model parameters of road intersections are obtained through feature extraction and model training using the deformable part models; Finally, the geometric position and geometric shape type of road intersections are obtained using sliding windows matching method. The result of simulation and experiment show that the new method can not only automatically and accurately detect the location of road intersections, but also achieve the geometric shape type of road intersections. Research in this method will effectively improve work efficiency of road network topology construction. |
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