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国土资源遥感  2013, Vol. 25 Issue (4): 72-78    DOI: 10.6046/gtzyyg.2013.04.12
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
基于Canny边缘检测算子的矿区道路提取
曾发明1, 杨波1, 吴德文2, 唐攀科2, 张建国2, 张鸿键1
1. 湖南师范大学GIS研究中心, 长沙 410081;
2. 有色金属矿产地质调查中心, 北京 100012
Extraction of roads in mining area based on Canny edge detection operator
ZENG Faming1, YANG Bo1, WU Dewen2, TANG Panke2, ZHANG Jianguo2, ZHANG Hongjian1
1. GIS Research Centre of Hunan Normal University, Changsha 410081, China;
2. China Non-ferrous Metals Resources Geological Survey, Beijing 100012, China
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摘要 

矿区道路作为矿区的主要运输通道,是采矿活动必需的组成要素。在空间结构上,矿区道路是其他要素的连接纽带,它们之间有着重要的空间拓扑关系——矿区通常由一条主要道路连接着开采面(矿硐)、选矿池、固体废弃物、工棚建筑和尾矿库等要素。通过对矿区道路的识别和提取,有助于建立地表采矿系统(surface mining system,SMS),对矿区进行遥感监测和自动遥感解译。利用高分辨率遥感图像,提出一种基于Canny边缘检测算子的矿区道路自动提取方法: 首先利用Canny算子对遥感图像进行边缘检测,得到边缘信息; 然后进行边缘匹配,判定道路边缘,从而对研究区内的道路进行定位和矢量化。利用该方法对某矿区道路进行提取实验的结果表明,该方法能快速提取矿区道路,具有较强的实用性。

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Abstract

As the main transport corridors of the mine,the roads in the mining area are very important parts of the mining activities. Spatially,the roads are the connection links of the other elements in the mining area, and there are important topological relationships between them:The major road usually connects such elements as the mining surface area (or mine adit), the processing pool, the solid waste mineral, the shed (or buildings) and the tailings. The extraction and recognition of the mine road are helpful to building the surface mining system(SMS),making it easy to monitor the mining area and get automatic interpretation of remote sensing. In order to extract the mine road,the authors used high-resolution remote sensing image and proposed an approach based on Canny edge detection operator for automatic extraction of the road in the mining area in this paper. Firstly, the road edges were extracted by using the Canny detector. Furthermore, the edge matching method was used to determine the road edges, which resulted in the quantization and positioning of the road vector in the study area. The methods proposed in this paper were used to extract the road in the mining area successfully. The results show that the proposed method is of very strong practical applicability.

Key wordstemperature vegetation dryness index(TVDI)    thermal inertia    relative soil water content    groundwater depth    MODIS    Yellow River Delta
收稿日期: 2013-01-23      出版日期: 2013-10-21
:  TP75  
基金资助:

国家自然科学基金(编号: 41171342)和湖南省高校创新平台开放基金(编号: 10K042)项目共同资助。

通讯作者: 杨波(1974- ),男,副教授,主要研究领域为资源环境与灾害遥感。E-mail: yb@hunnu.edu.cn
作者简介: 曾发明(1987- ),男,硕士研究生,主要研究方向为资源环境遥感。E-mail: junkai1314@126.com。
引用本文:   
曾发明, 杨波, 吴德文, 唐攀科, 张建国, 张鸿键. 基于Canny边缘检测算子的矿区道路提取[J]. 国土资源遥感, 2013, 25(4): 72-78.
ZENG Faming, YANG Bo, WU Dewen, TANG Panke, ZHANG Jianguo, ZHANG Hongjian. Extraction of roads in mining area based on Canny edge detection operator. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(4): 72-78.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2013.04.12      或      https://www.gtzyyg.com/CN/Y2013/V25/I4/72
[1] 程江华,高 贵,库锡树,等.SAR图像道路网提取方法综述[J].中国图象图形学报,2013,18(1):11-23. Cheng J H,Gao G,Ku X S,et al.Review of road network extraction from SAR images[J].Journal of Image and Graphics,2013,18(1):11-23.
[2] 叶发茂,苏林,李树楷,等.高分辨率遥感影像提取道路的方法综述与思考[J].国土资源遥感,2006,18(1):12-17. Ye F M,Su L,Li S K,et al.Review and thought of road extraction from high resolution remote sensing images[J].Remote Sensing for Land and Resources,2006,18(1):12-17.
[3] 卢昭羿,左小清,黄亮,等.面向对象的投影互分割道路变化检测[J].国土资源遥感,2012,24(3): 60-64. Lu Z Y,Zuo X Q,Huang L,et al.Road change detection using object-oriented projective interactive partition[J].Remote Sensing for Land and Resources,2012,24(3):60-64.
[4] 张睿,张继贤,李海涛.基于角度纹理特征及剖面匹配的高分辨率遥感影像带状道路半自动提取[J].遥感学报,2008,12(2):224-232. Zhang R,Zhang J X,Li H T.Semi-automatic extraction of ribbon roads from high resolution remotely sensed imagery based on angular texture signature and profile match[J].Journal of Remote Sensing,2008,12(2):224-232.
[5] 雷小奇,王卫星,赖均.一种基于形状特征进行高分辨率遥感影像道路提取方法[J].测绘学报,2009,38(5):457-465. Lei X Q,Wang W X,Lai J.A method of road extraction from high resolution remote sensing images based on shape features[J].Acta Geodaetica et Cartographica Sinica,2009,38(5):457-465.
[6] 李怡静,胡翔云,张剑清,等.影像与LiDAR数据信息融合复杂场景下的道路自动提取[J].测绘学报,2012,41(6):870-876. Li Y J,Hu X Y,Zhang J Q,et al.Automatic road extraction in complex scenes based on information fusion from LiDAR data and remote sensing imagery[J].Acta Geodaetica et Cartographica Sinica,2012,41(6):870-876.
[7] 宁亚辉,雷小奇,王功孝,等.Dempster-Shafer证据融合形状特征的高分辨率遥感图像道路信息提取[J].中国图象图形学报,2011,16(12):2183-2190. Ning Y H,Lei X Q,Wang G X,et al.Road extraction from high-resolution remote sensing images based on Dempster-Shafer evidence theory and fusion shape features[J].Journal of Image and Graphics,2011,16(12):2183-2190.
[8] Wiedemann C,Mayer H.Automatic verification of roads in digital images using profiles[M].Berlin:Springer Berlin Heidelberg,1996:609 - 618.
[9] Rellier G,Descombes X,Zerubia J.Local registration and deformation of a road cartographic database on a SPOT satellite image[J].Pattern Recognition,2002,35(10):2213-2221.
[10] Doucette P,Agouris P,Stefanidis A.Automated road extraction from high resolution multispectral imagery[J].Photogrammetric Engineering and Remote Sensing,2004(12):1405-1416.
[11] Dal-Poz A P,Vale G M D,Zanin R B.Automatic extraction of road seeds from high-resolution aerial images[J].Annals of the Brazilian Academy of Sciences,2005,77(3):509-520.
[12] Ye F,Lin S,Tang J.Automatic road extraction using particle filters from high resolution images[J].Journal of China University of Mining and Technology,2006,16(4):490-493.
[13] 吕健刚,韦春桃.基于Hough变换的高分辨率遥感影像城市直线道路提取[J].遥感信息,2009(3):15-18. Lyu J G,Wei C T.Urban straight road extraction from high resolution remote sensing image based on Hough transform[J].Remote Sensing Information,2009(3):15-18.
[14] 董占杰,毛政元.基于道路绿地特征的遥感影像道路信息提取方法研究[J].国土资源遥感,2011,23(2):43-46. Dong Z J,Mao Z Y.Methodological research on road extraction based on characteristics of road greenbelts in remotely sensed imagery[J].Remote Sensing for Land and Resources,2011,23(2):43-46.
[15] 许高程,毕建涛,王星星,等.面向对象的高分辨率遥感影像道路自动提取实验[J].遥感信息,2012(2):108-111. Xu G C,Bi J T,Wang X X,et al.An experiment of automatic road extraction from high-resolution remote sensing image based on object-oriented technology[J].Remote Sensing Information,2012(2):108-111.
[16] Jin H,Miska M,Chung E,et al.Road feature extraction from high resolution aerial images upon rural regions based on multi-resolution image analysis and Gabor filters[J].Remote Sensing:Advanced Techniques And Platforms,2012:387-416
[17] Canny J.A computational approach to edge detection[J].IEEE Transaction on pattern Analysis and Machine Intelligence,1986,8(6):679-698.
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