等高线预处理技术的研究
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摘要
地图数字化是地理信息系统(GIS)的重要研究环节。现有的纸质地图转换为电子地图，即地图矢量化是当前比较重要的工作。而在地图中大量的等高线被用于描述三维地形信息，等高线的预处理工作更为紧迫，并且它也是生成DEM数据的一种有效方法。本文以1：5000的彩色地形图为研究对象，重点对等高线的提取进行了探索。
本文首先讨论了颜色空间及空间的转换方法，仔细研究了彩色地图图像数据，归纳出彩色地图图像颜色的特点。认真研究了国内外彩色地图分色方法，对现有的分色算法进行了认真的总结和归纳，并在此基础上，提出一种新的分色方法：在颜色判断公式中增加了象素的亮度因素作为辅助条件，同时与地图空间关系信息相结合的分色方法。
针对等高线本身的特点，对Zhang快速并行细化算法进行分析和改进，考虑了对称性和运行速度问题，提出了适用于等高线细化的算法。
由于图纸、扫描、地物压盖、颜色误差等诸多因素的影响，包含等高线的棕版图存在不少断裂，这给等高线栅格数据到矢量数据转换带来了很大的困难。本文在得到线划要素的细化骨架线后，利用变步长跟踪法，不仅减少了搜索的次数，而且轮廓识别准确，当遇到断点时，自动增加步长跨越断点。同时实现了边跟踪边压缩。
最后，结束语部分对前面所做的工作进行了总结，并对地图数字化的现状和未来的发展状况进行了阐述。
Topographic contour line is one of the key tasks in GIS development.The conversion of maps from paper into digital, namely map-vectorization is very important. In topographic maps, contour lines are the most important features to characterize three-dimensional terrain on two-dimensional map sheets, so its pretreatment of the contour line is in urgent. In this paper an effective method for extracting contour lines from color scanned topographical maps is proposed. This paper takes color emphasizes map with a scale of 1:5000 as the research on the recognition and acquisition of contour line.
Firstly, color model, its conversion is discussed thoroughly, the data of color map image is studied carefully and the color characteristic of color map image is induced thoroughly. The algorithm of color separation is researched earnestly and valued rightly. At last ,the new method is put forward to: the method based on RGB color model and image spatial relativity to get the result we want.
Aiming at the characteristic of contour lines, an analysis and improvement of the Zhang fast parallel thinning algorithm is presented, considering both the symmetry and operating speed, and an adaptive algorithm of contour lines thinning is brought forward.
The brown map that includes contour lines has many conglutinations and ruptures due to the map own quality, scanned effect, overlay of other map objects. Because of the bad quality of contour line map, the work of contour lines extraction and recognition from color map becomes very hard. Achieving the thinned contour lines of lined constituents, the adoption of tracking method based on varying step lengths not only reduces the searching times, but also makes the contour identification more precise. When encounters broken point, the step length increases automatically to span it. At the same time enables the tracking and compressing to be simultaneous.
Finally ,the research work in this thesis is concluded .status and development of the map digitalization are described.
本文首先讨论了颜色空间及空间的转换方法，仔细研究了彩色地图图像数据，归纳出彩色地图图像颜色的特点。认真研究了国内外彩色地图分色方法，对现有的分色算法进行了认真的总结和归纳，并在此基础上，提出一种新的分色方法：在颜色判断公式中增加了象素的亮度因素作为辅助条件，同时与地图空间关系信息相结合的分色方法。
针对等高线本身的特点，对Zhang快速并行细化算法进行分析和改进，考虑了对称性和运行速度问题，提出了适用于等高线细化的算法。
由于图纸、扫描、地物压盖、颜色误差等诸多因素的影响，包含等高线的棕版图存在不少断裂，这给等高线栅格数据到矢量数据转换带来了很大的困难。本文在得到线划要素的细化骨架线后，利用变步长跟踪法，不仅减少了搜索的次数，而且轮廓识别准确，当遇到断点时，自动增加步长跨越断点。同时实现了边跟踪边压缩。
最后，结束语部分对前面所做的工作进行了总结，并对地图数字化的现状和未来的发展状况进行了阐述。
Topographic contour line is one of the key tasks in GIS development.The conversion of maps from paper into digital, namely map-vectorization is very important. In topographic maps, contour lines are the most important features to characterize three-dimensional terrain on two-dimensional map sheets, so its pretreatment of the contour line is in urgent. In this paper an effective method for extracting contour lines from color scanned topographical maps is proposed. This paper takes color emphasizes map with a scale of 1:5000 as the research on the recognition and acquisition of contour line.
Firstly, color model, its conversion is discussed thoroughly, the data of color map image is studied carefully and the color characteristic of color map image is induced thoroughly. The algorithm of color separation is researched earnestly and valued rightly. At last ,the new method is put forward to: the method based on RGB color model and image spatial relativity to get the result we want.
Aiming at the characteristic of contour lines, an analysis and improvement of the Zhang fast parallel thinning algorithm is presented, considering both the symmetry and operating speed, and an adaptive algorithm of contour lines thinning is brought forward.
The brown map that includes contour lines has many conglutinations and ruptures due to the map own quality, scanned effect, overlay of other map objects. Because of the bad quality of contour line map, the work of contour lines extraction and recognition from color map becomes very hard. Achieving the thinned contour lines of lined constituents, the adoption of tracking method based on varying step lengths not only reduces the searching times, but also makes the contour identification more precise. When encounters broken point, the step length increases automatically to span it. At the same time enables the tracking and compressing to be simultaneous.
Finally ,the research work in this thesis is concluded .status and development of the map digitalization are described.
引文
[1] 郝向阳．地图信息识别与提取技术[M]．北京．测绘出版社，2001．
[2] 郭玲等．如何在STAGE中增加用户模块[J]．力与指挥控制年会论文2001．
[3] 郑海鹰．计算机地图制图原理[M]．郑州：解放军信息工程大学，2000．
[4] 修文群等．城市地理信息系统[M]．北京：北京希望电脑公司出版社，1999．
[5] 徐青，郝向阳．GIS数据的获取与质量分析[M]．北京：解放军出版社，1999．
[6] 龚健雅．地理信息系统基础[M]．北京：科学出版社，2001．
[7] 吴信才．地理信息系统原理与方法[M]．北京：电子工业出版社，2002．
[8] 高俊，夏运钧．虚拟现实在地形环境仿真中的应用[M]．北京：解放军出版社，1999．
[9] 滕树钦．地图分层矢量化的研究与实现[D]．硕士学位论文，南京理工大学，2002．
[10] 陈述彭等．地理信息系统导论[M]．北京：科学出版社，2001年．
[11] 郝向阳．地图信息识别与提取技术的研究与实践[D]．博士学位论文，解放军测绘学院，1996年．
[12] 汤顺青．色度学[M]．北京：北京理工大学出版社，1988．12．
[13] 郭新平．真彩色数字图像在VGA上的显示．微计算机应用，1993．5．
[14] 陈元琰，张晓竞．计算机图形学实用技术[M]．北京：科学出版社．2000，308～311
[15] 白轶多．扫描地图的等高线自动提取[D]．硕士学位论文，武汉大学，2005．
[16] 曾迎生．地图图符提取与识别算法研究[D]．博士学位论文，国防科学技术大学，2003．
[17] 王柳．彩色扫描地图上的等高线提取及处理[D]．硕士学位论文，武汉大学，2001．
[18] 杨旭．彩色地图图像分色技术的研究[D]．硕士学位论文，解放军信息工程大学，2001．
[19] 王福生，齐国清．二值图像中目标物体轮廓的边界跟踪算法[J]．大连海事大学学报．2006第32卷第1期．
[20] 李岩影，过静君．等高线扫描图像的高校自适应识别方法[J]．北京测绘， 2001，2(1)：9．12．
[21] 缪绍刚．数字图像处理-活用Maflab[M]，成都：西南交通大学出版社，2001，
[22] 郭玲，王晓兰，周献中．结合颜色特征和结构特征的彩色地图分层算法[J]．计算机辅助设计与图形学学报，2003，15(12)：1463-1467．
[23] 葛永慧，潘尚龙，余哲．扫描地形图线状要素的自动提取[J]．山西矿业学院学报，1996，14(2)：109～112．
[24] 黄文骞．彩色地图图像的自动分色[J]．武汉测绘科技大学学报，1998年第23卷第3期．
[25] 金聪 彭嘉雄．利用遗传算法实现数字图像分割[J]．小型微型计算机系统2002年，第23卷第7期．
[26] 郑华利，周献忠，王建宇．空间关系信息和颜色信息相结合的地形图分层算法[J]．中国图像图形学报，2003年，第8卷((A版)第3期．
[27] 高新波，谢维信．模糊聚类理论发展及应用的研究进展[J]．科学通报，1999年第21期．
[28] 钱静．彩色地形图中等高线提取方法的研究[D]．硕士学位论文，国防科学技术大学，2005．
[29] 陈国栋，张树有．工程图像数字化转换与智能理解[M]．北京：机械工业出版社，2001．5．．
[30] 何斌等．Visual C++数字图像处理(第二版)[M]．北京：人民邮电出版社，2002．
[31] 井元伟，李海燕．一种改进的等高线并行细化算法[J]．东北大学学报(自然科学版)，2006．9．
[32] 吕岳，施鹏飞．一种实用并行细化算法及其实现[J]．计算机工程与设计，2000，21(4)：53-56．
[33] 董立菊，于戈．基于噪声图像2D直方图的快速分割方法[J]．东北大学学报(自然科学版)，2005，26(3)：220-223。
[34] 吕俊白．一种有效的二值图像细化算法[J]．计算机工程，2003，29(18)：147-148．
[35] D. Greenlee. Raster and Vector processing for scanned line work. Photogrammetric Engineering and Remote Sensing, 1987, 53(10): 1383-1387.
[36] T. Amin, R. Kasturi. Map data processing: Recognition of lines and symbols. OpticalEngineering, 1987,26(4):354-358.
[37] M.Ansoult, P.Soille, J.Loodts. Mathematical morphology: a tool for automated GIS dataacquisition from scanned thematic maps. Photogrammetric Engineering and Remote Sensing,56(9):1263-1271.
[38] Seong Whan. Direct extraction of topographic features for gray scale character recognition.IEEE Transactions on PAMI,1995,17(7):724-729.
[39] Fang B K,Chin R T. Analysis of thining algorithms using mathematical morphology[J]. IEEE Trans PAM1,1990,12(6).
[40] Sternberg S R. Grayscale Morphology [J]. Computics, and Image Processing, 1986 35(1):333-355.
[41] Stentiford, F.W. M. and R. G Mortimer. Some New Heuristics for Thining Binary Handprinted CharactersforOCR. IEEE Transactions on Systems, Man and Cybernetics 13(1):81-84.
[42] HallR W. Optimally small operator supports for fully parall thinning galgorithms [J]. IEEE Transactions on Pattern Analysisand and Machine Intelligence, 1993, 15(8): 828-833.
[43] S.Spinello, GGreiner. Automatic Contour line Recognition From Scanned Topographic Maps, Poster section, Fifth International Conference on Curves and Surfaces, Saint-Malo, France, June 27-July 3,2002.
[44] Arcelli C, Baja G..A one pass twcroperation process to detect the skeletal pixels on the 4 distance transform[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(4):411-414.
[45] Andrew and K.Skldmore, Terrain position as mapped from a ridded digital elevation model ljGIS,1990,4(1):33-36.
[46] Zhang T Y, Suen C Y. A fast parallel algorithm for thinning digital patterns[J].Communications of the ACM, 1984,27 (3):236-239.
[47] Lam L, Suen C Y. An evaluation of parallel thinning algorithms for character recognition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995,17(9):914-919.
[48] Arcelli C, Shanniti G..A width-independent fast thinning algorithm[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1985, 10(7): 463-47.
[49] J Hershberger and J Snoeyink. Speeding, up the Douglas-Peucker line simplification algorithm. In Proc. 5th Intl. Symp. Spatial Data Handing. IGU Commission on GIS, 1992: 134-143.
[50] Hoseph S H, Pridmore T P. Knowledge-based interpretation of mechanical engineering drawings[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(9): 928-941.
[2] 郭玲等．如何在STAGE中增加用户模块[J]．力与指挥控制年会论文2001．
[3] 郑海鹰．计算机地图制图原理[M]．郑州：解放军信息工程大学，2000．
[4] 修文群等．城市地理信息系统[M]．北京：北京希望电脑公司出版社，1999．
[5] 徐青，郝向阳．GIS数据的获取与质量分析[M]．北京：解放军出版社，1999．
[6] 龚健雅．地理信息系统基础[M]．北京：科学出版社，2001．
[7] 吴信才．地理信息系统原理与方法[M]．北京：电子工业出版社，2002．
[8] 高俊，夏运钧．虚拟现实在地形环境仿真中的应用[M]．北京：解放军出版社，1999．
[9] 滕树钦．地图分层矢量化的研究与实现[D]．硕士学位论文，南京理工大学，2002．
[10] 陈述彭等．地理信息系统导论[M]．北京：科学出版社，2001年．
[11] 郝向阳．地图信息识别与提取技术的研究与实践[D]．博士学位论文，解放军测绘学院，1996年．
[12] 汤顺青．色度学[M]．北京：北京理工大学出版社，1988．12．
[13] 郭新平．真彩色数字图像在VGA上的显示．微计算机应用，1993．5．
[14] 陈元琰，张晓竞．计算机图形学实用技术[M]．北京：科学出版社．2000，308～311
[15] 白轶多．扫描地图的等高线自动提取[D]．硕士学位论文，武汉大学，2005．
[16] 曾迎生．地图图符提取与识别算法研究[D]．博士学位论文，国防科学技术大学，2003．
[17] 王柳．彩色扫描地图上的等高线提取及处理[D]．硕士学位论文，武汉大学，2001．
[18] 杨旭．彩色地图图像分色技术的研究[D]．硕士学位论文，解放军信息工程大学，2001．
[19] 王福生，齐国清．二值图像中目标物体轮廓的边界跟踪算法[J]．大连海事大学学报．2006第32卷第1期．
[20] 李岩影，过静君．等高线扫描图像的高校自适应识别方法[J]．北京测绘， 2001，2(1)：9．12．
[21] 缪绍刚．数字图像处理-活用Maflab[M]，成都：西南交通大学出版社，2001，
[22] 郭玲，王晓兰，周献中．结合颜色特征和结构特征的彩色地图分层算法[J]．计算机辅助设计与图形学学报，2003，15(12)：1463-1467．
[23] 葛永慧，潘尚龙，余哲．扫描地形图线状要素的自动提取[J]．山西矿业学院学报，1996，14(2)：109～112．
[24] 黄文骞．彩色地图图像的自动分色[J]．武汉测绘科技大学学报，1998年第23卷第3期．
[25] 金聪 彭嘉雄．利用遗传算法实现数字图像分割[J]．小型微型计算机系统2002年，第23卷第7期．
[26] 郑华利，周献忠，王建宇．空间关系信息和颜色信息相结合的地形图分层算法[J]．中国图像图形学报，2003年，第8卷((A版)第3期．
[27] 高新波，谢维信．模糊聚类理论发展及应用的研究进展[J]．科学通报，1999年第21期．
[28] 钱静．彩色地形图中等高线提取方法的研究[D]．硕士学位论文，国防科学技术大学，2005．
[29] 陈国栋，张树有．工程图像数字化转换与智能理解[M]．北京：机械工业出版社，2001．5．．
[30] 何斌等．Visual C++数字图像处理(第二版)[M]．北京：人民邮电出版社，2002．
[31] 井元伟，李海燕．一种改进的等高线并行细化算法[J]．东北大学学报(自然科学版)，2006．9．
[32] 吕岳，施鹏飞．一种实用并行细化算法及其实现[J]．计算机工程与设计，2000，21(4)：53-56．
[33] 董立菊，于戈．基于噪声图像2D直方图的快速分割方法[J]．东北大学学报(自然科学版)，2005，26(3)：220-223。
[34] 吕俊白．一种有效的二值图像细化算法[J]．计算机工程，2003，29(18)：147-148．
[35] D. Greenlee. Raster and Vector processing for scanned line work. Photogrammetric Engineering and Remote Sensing, 1987, 53(10): 1383-1387.
[36] T. Amin, R. Kasturi. Map data processing: Recognition of lines and symbols. OpticalEngineering, 1987,26(4):354-358.
[37] M.Ansoult, P.Soille, J.Loodts. Mathematical morphology: a tool for automated GIS dataacquisition from scanned thematic maps. Photogrammetric Engineering and Remote Sensing,56(9):1263-1271.
[38] Seong Whan. Direct extraction of topographic features for gray scale character recognition.IEEE Transactions on PAMI,1995,17(7):724-729.
[39] Fang B K,Chin R T. Analysis of thining algorithms using mathematical morphology[J]. IEEE Trans PAM1,1990,12(6).
[40] Sternberg S R. Grayscale Morphology [J]. Computics, and Image Processing, 1986 35(1):333-355.
[41] Stentiford, F.W. M. and R. G Mortimer. Some New Heuristics for Thining Binary Handprinted CharactersforOCR. IEEE Transactions on Systems, Man and Cybernetics 13(1):81-84.
[42] HallR W. Optimally small operator supports for fully parall thinning galgorithms [J]. IEEE Transactions on Pattern Analysisand and Machine Intelligence, 1993, 15(8): 828-833.
[43] S.Spinello, GGreiner. Automatic Contour line Recognition From Scanned Topographic Maps, Poster section, Fifth International Conference on Curves and Surfaces, Saint-Malo, France, June 27-July 3,2002.
[44] Arcelli C, Baja G..A one pass twcroperation process to detect the skeletal pixels on the 4 distance transform[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(4):411-414.
[45] Andrew and K.Skldmore, Terrain position as mapped from a ridded digital elevation model ljGIS,1990,4(1):33-36.
[46] Zhang T Y, Suen C Y. A fast parallel algorithm for thinning digital patterns[J].Communications of the ACM, 1984,27 (3):236-239.
[47] Lam L, Suen C Y. An evaluation of parallel thinning algorithms for character recognition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995,17(9):914-919.
[48] Arcelli C, Shanniti G..A width-independent fast thinning algorithm[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1985, 10(7): 463-47.
[49] J Hershberger and J Snoeyink. Speeding, up the Douglas-Peucker line simplification algorithm. In Proc. 5th Intl. Symp. Spatial Data Handing. IGU Commission on GIS, 1992: 134-143.
[50] Hoseph S H, Pridmore T P. Knowledge-based interpretation of mechanical engineering drawings[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(9): 928-941.