沥青路面检测中的图像处理技术研究
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摘要
随着我国经济的蓬勃发展,交通运输事业也随之取得了令人瞩目的成就,其中,高速公路的总里程已经跃居世界第二。对数量如此庞大的公路资源进行有效管理和维护,必须迅速提高路面检测技术的整体水平。大型成套检测设备是检测技术水平的具体体现,它们的应用对我国交通事业的长远发展有深远影响,对整个国民经济的发展也意义重大。
本文主要对沥青路面行车性能激光检测系统中的图像处理技术展开研究,采用理论与试验手段相结合的研究方法,重点论述了路面图像分析、路面轮廓数据管理以及路面模型重构等方面的核心技术。
文中首先介绍检测系统的总体实现方案,并对主要硬件的组成情况以及软件架构作了概述。随后,着重讨论了路面图像的处理和分析技术,通过对比与综合,提出一种高精度的复合细化算法。该算法的主要步骤分两步:1)分别采用阈值分割和灰度邻域属性法消除白噪声及孤点噪声;2)使用B样条拟合重心法完成图像的细化工作。
本文还阐述了基于NetCDF格式的轮廓数据管理方案,它区别于关系数据库系统,对路面分析数据的存储有更优的效率。在方案实现上,借助多线程及缓冲区预存技术充分减小数据的存储延时以提高系统的整体性能。最后,详细论述了基于细分的Hoppe方法实现路面模型重构的原理及特点,对于如何利用OpenGL结合MFC开发模型实现重构算法,也作了简要的讨论并给出相关的主要程序。
通过模拟试验及典型的数据测试,证明了本文采用的路面图像细化算法、分析数据管理方案和路面模型重构方法的可行性和有效性,可以应用于本文所提及的检测设备及其他同类型的设备中。
With the rapid development of national economy, domestic transportation industry has attained prominent achievements among which the total mileage of highway has already ranked second in the world. It is necessary to upgrade the pavement surface detecting technique generally so that such numerous highway resources are maintained properly. Large-scale complete set detecting equipments are embodiment of detecting techniques;therefore, their application has profound influence on the long-term development of communication in our country and is supposed to be significant to domestic economy.This dissertation focuses on the image processing and analyzing techniques indeveloping Laser Inspecting System for Driving Property of Asphalt Pavement(LDSDPAP). Having implemented a method combining theory with experiment, itmainly describes core techniques on pavement image analysis, analysis datamanagement and reconstruction of 3D pavement model.First, this dissertation concisely introduces the scheme of detecting system, main hardware structure and software architecture. Second, it particularizes the pavement image processing and analyzing techniques and a high precision hybrid thinning algorithm has been proposed through comparison and synthesis. The algorithm includes two major phases: 1) removing white noise and acnode noise by threshold segmentation and grayscale neighborhood property respectively;2) using B-Spline based barycenter algorithm to finish the pavement image thinning.Third, a NetCDF based analysis data management plan has been discussed. It differs from the relational database system in efficiency of storing pavement analysis data and characterizes an implementation with a minimum delay using multithreading and buffer prefetching techniques to improve the performance of whole system.Finally, there is a full discussion of concept and features of Hoppe method based on subdivision for pavement model reconstruction and an explanation of key parts about how to program reconstruction module combining OpenGL with MFC. Meanwhile, the related coding sections are also presented for demonstration.Being testified by simulation and typical data, the pavement image thinning algorithm, analysis data management plan and pavement model reconstruction method are proved to be feasible and effective. Hence, they can be applied to LDSDPAP and other similar systems.
本文主要对沥青路面行车性能激光检测系统中的图像处理技术展开研究,采用理论与试验手段相结合的研究方法,重点论述了路面图像分析、路面轮廓数据管理以及路面模型重构等方面的核心技术。
文中首先介绍检测系统的总体实现方案,并对主要硬件的组成情况以及软件架构作了概述。随后,着重讨论了路面图像的处理和分析技术,通过对比与综合,提出一种高精度的复合细化算法。该算法的主要步骤分两步:1)分别采用阈值分割和灰度邻域属性法消除白噪声及孤点噪声;2)使用B样条拟合重心法完成图像的细化工作。
本文还阐述了基于NetCDF格式的轮廓数据管理方案,它区别于关系数据库系统,对路面分析数据的存储有更优的效率。在方案实现上,借助多线程及缓冲区预存技术充分减小数据的存储延时以提高系统的整体性能。最后,详细论述了基于细分的Hoppe方法实现路面模型重构的原理及特点,对于如何利用OpenGL结合MFC开发模型实现重构算法,也作了简要的讨论并给出相关的主要程序。
通过模拟试验及典型的数据测试,证明了本文采用的路面图像细化算法、分析数据管理方案和路面模型重构方法的可行性和有效性,可以应用于本文所提及的检测设备及其他同类型的设备中。
With the rapid development of national economy, domestic transportation industry has attained prominent achievements among which the total mileage of highway has already ranked second in the world. It is necessary to upgrade the pavement surface detecting technique generally so that such numerous highway resources are maintained properly. Large-scale complete set detecting equipments are embodiment of detecting techniques;therefore, their application has profound influence on the long-term development of communication in our country and is supposed to be significant to domestic economy.This dissertation focuses on the image processing and analyzing techniques indeveloping Laser Inspecting System for Driving Property of Asphalt Pavement(LDSDPAP). Having implemented a method combining theory with experiment, itmainly describes core techniques on pavement image analysis, analysis datamanagement and reconstruction of 3D pavement model.First, this dissertation concisely introduces the scheme of detecting system, main hardware structure and software architecture. Second, it particularizes the pavement image processing and analyzing techniques and a high precision hybrid thinning algorithm has been proposed through comparison and synthesis. The algorithm includes two major phases: 1) removing white noise and acnode noise by threshold segmentation and grayscale neighborhood property respectively;2) using B-Spline based barycenter algorithm to finish the pavement image thinning.Third, a NetCDF based analysis data management plan has been discussed. It differs from the relational database system in efficiency of storing pavement analysis data and characterizes an implementation with a minimum delay using multithreading and buffer prefetching techniques to improve the performance of whole system.Finally, there is a full discussion of concept and features of Hoppe method based on subdivision for pavement model reconstruction and an explanation of key parts about how to program reconstruction module combining OpenGL with MFC. Meanwhile, the related coding sections are also presented for demonstration.Being testified by simulation and typical data, the pavement image thinning algorithm, analysis data management plan and pavement model reconstruction method are proved to be feasible and effective. Hence, they can be applied to LDSDPAP and other similar systems.
引文
[1] 王吉林,杜文靖,王国强.沥青路面检测技术现状.交通科技与经济,2003,3:1～4
[2] 梁新政,潘卫育,徐宏.路面无损检测技术新发展.公路学报,2002,9:27～31
[3] 尤占平.沥青路面车辙及其评价.云南交通科技,1999,15(6):22～44
[4] 王荣本,王超,初秀民.路面破损图像识别研究进展.吉林大学学报(工学版),2002,32(4):91～96
[5] 初秀民,王荣本,储江伟.沥青路面破损图像分割方法研究.中国公路学报,2003,16(3),11～14
[6] 中华人民共和国交通部.JTJ 001-97.公路工程技术标准.北京:人民交通出版社,1997
[7] 王端宜,李维杰,张肖宁.用数字图像技术评价和测量沥青路表面构造深度.华南理工大学学报(自然科学版),2004,32(2):42～45
[8] 石教英,蔡文立.科学计算可视化算法与系统.北京:科学出版社.1996
[9] 吕永刚.CAGD自由曲线曲面造型中均匀样条的研究:[博士学位论文].浙江:浙江大学理学院,2002
[10] 乔玉晶.结构光截面轮廓测量系统的研究:[硕士学位论文].哈尔滨:哈尔滨理工大学,2003
[11] 章毓晋.图像工程(上册):图像处理和分析.北京:清华大学出版社,1999
[12] 章毓晋.图像分割.北京:科学出版社,2001
[13] Erich Gamma,Richard Helm,Ralph Johnson,et al.设计模式:可复用面向对象软件的基础(李英军,马晓星,蔡敏等).北京:机械工业出版社,2000
[14] 贺俊吉,张广军.结构光三维视觉检测中光条图像处理方法研究.北京航空航天大学学报,2003,29(7):593～597
[15] 雷海军,李德华,王建永等.一种结构光条纹中心快速检测方法.华中科技大学学报(自然科学版),2003,31(1):74～76
[16] 王爱囡.粗糙表面散射光强分布的特征参数研究.合肥工业大学学报(自然科学版),2002,25(6):1249～1251
[17] 艾勇.最新光学应用测量技术.武汉:武汉测绘大学出版社,1994
[18] 陈青山,吕乃光,燕必希等.激光准直高斯光斑中心位置计算方法分析.计算机测量与控制,2004,12(15):486～488
[19] 隋连升,李兵,蒋庄德.基于NURBS曲线插值的激光光刀图像中心提取方法的研究.中国激光,2003,29(7):593～597
[20] 解则晓,张成国,张国雄.基于B样条迭代法的激光光条噪声去除技术研究.光学技术,2005,31(3):430～433
[21] Jim Beveridge,Robert Wiener.Win32多线程程序设计一线程完全手册(侯捷).武汉:华中科技大学出版社,2002
[22] 朱心雄.自由曲线曲面造型技术.北京:科学出版社,2000
[23]D onald Hearn, M. Pauline Baker.计算机图形学(蔡士杰,吴春镕,孙正兴等)北京: 电子工业出版社,2002
[24] 孙正兴,周良,郑宏源.计算机图形学基础教程.北京:清华大学出版社,2004
[25] 李胜瑞,王乘恩,王智高.计算机图形学试验教程(OpenGL版).北京:机械工业出版社,2004
[26] 尚游,张双,万磊等.OpenGL高级图形编程指南.哈尔滨:哈尔滨工程大学出版社,1999
[27] Eugene Olafsen,Kenn Scribner, K. David White,et al.MFC Visual C++6编程技术内幕(王建华,陈一飞,张焕生等).北京:机械工业出版社,2000
[28] Hu GongZhu, Gorge Stonman. 3D surface solution using structured light and constraint propagation. IEEE-PAMI, 1995, 11(4), 225～231
[29] A Rosenfeld, A C Kak. Digital Picture Processing. US: Academic Press, 1982
[30] Haralick R M, Shapiro I G, Image segmentation techniques. CVGIP, 1985, 29:100～132
[31] W Doyle. Operations useful for similarity-invariant pattern recognition. Journal of the ACM, 1962, 9(2): 259～267
[32] Deng Wenyi, Lu Naiguang, Zhuang Jingcheng, et al. A stereo vision system for measurement of 3D object. SPIE, 1998, 3558:248～525
[33] M A Sid-Ahmed, M T Boraie. Dual camera calibration for 3D machine vision. IEEE-Transaction on Instruction and Measurement, 1990, 39(4): 512～516
[34] Siriphan Jitprasithsiri. Development of a new digital pavement image processing algorithm for unified crack index computation: [PhD. thesis]. US: University of Utah, 1997
[35] Koutsopoulos H N, Downey A B. Primitive-based classification of pavement cracking images. Journal of Transportation Engineering, 1993, 119(3): 402～418
[36] Chou Jaching, O'Neill, Wende A, et al. Pavement distress evaluation using fuzzy logic and moment invariants. Transportation Research Record, 1995, 1505: 39～46
[37] Kaseko M S, Lo Z P, Ritchie S G. Comparison of Traditional and Neural Classifiers for Pavement Crack Detection. Journal of Transportation Engineering, ASCE, 1994, 120(4): 552～569.
[38] Cheng H D, Chen J R, Glazier C, et al. Novel approach to pavement cracking detection based on fuzzy set theory. Journal of Computing in Civil Engineering, 1999, 13(44): 270～280
[39] Cheng HengDa. Automated real-time pavement distress detection using fuzzy logic and neural network. SPIE Proceedings, 1996, 2946:140～151
[40] M Miyojim, H D Cheng. Novel System for Automatic Pavement Distress Detection. ASCE, 1998, 12(3): 145～152
[41] Horn B K P. Shape from shading: a method for obtaining the shape of a smooth opaque object from one view. MIT AI Laboratory Technical Report 232. Massachusetts: MIT, 1970
[42] ChunJung Hsu, ChiFarn Chen, Chao Lee, et al. Airport pavement distress image classification using moment invariant neural network. In: S C Lie weds, Proceedings of 22nd Asian Conference on Remote Sensing. Singapore: National University of Singapore, 2001, 216-220
[43] Milan Sonka, Valcav Hlavac, Roger Boyle. Image Processing, Analysis and Machine Vision (Photocopy). Beijing: Post and Telecom Press, 2002
[44] Sun Microsystems Inc. 1014. The Request for Comments. US: Internet Engineering Task Force and the Internet Engineering Steering Group, 1997
[45] M Eck, H Hoppe. Automatic reconstruction of B-spline surfaces of arbitrary topological type. Computer Graphics, 1996: 325-334
[46] H Hoppe, T DeRose, T Duchamp, et al. Surface reconstruction from unorganized points. Computer Graphics, 1992, 26(2): 71-78
[47] E Allgower, P Schmidt. An Algorithm for Piecewise-Linear Approximation of an Implicitly Defined Manifold. SIAM, Journal of Numerical Analysis, 1985,22(2): 322-346
[48] Charles Loop. Smooth subdivision surfaces based on triangles: [Master's thesis]. US: Department of Computer Science and Engineering, University of Washington, 1987
[49] H Hoppe, T DeRose, T Duchamp, et al. Mesh optimization. Computer Graphics (SIGGRAPH '93 Proceedings), 1993: 19-26
[50] Hugues Hoppe. Surface reconstruction from unorganized points: [PhD. thesis]. US: Department of Computer Science and Engineering, University of Washington, 1994
[51] Jackie Neider, Tom Davis. OpenGL Programming Guide. US: Addison-Wesley Publishing Company, 1997
[52] Dale Rogerson. OpenGL I: Quick Start. US: Microsoft Developer Network Technology Group, 1994
[2] 梁新政,潘卫育,徐宏.路面无损检测技术新发展.公路学报,2002,9:27～31
[3] 尤占平.沥青路面车辙及其评价.云南交通科技,1999,15(6):22～44
[4] 王荣本,王超,初秀民.路面破损图像识别研究进展.吉林大学学报(工学版),2002,32(4):91～96
[5] 初秀民,王荣本,储江伟.沥青路面破损图像分割方法研究.中国公路学报,2003,16(3),11～14
[6] 中华人民共和国交通部.JTJ 001-97.公路工程技术标准.北京:人民交通出版社,1997
[7] 王端宜,李维杰,张肖宁.用数字图像技术评价和测量沥青路表面构造深度.华南理工大学学报(自然科学版),2004,32(2):42～45
[8] 石教英,蔡文立.科学计算可视化算法与系统.北京:科学出版社.1996
[9] 吕永刚.CAGD自由曲线曲面造型中均匀样条的研究:[博士学位论文].浙江:浙江大学理学院,2002
[10] 乔玉晶.结构光截面轮廓测量系统的研究:[硕士学位论文].哈尔滨:哈尔滨理工大学,2003
[11] 章毓晋.图像工程(上册):图像处理和分析.北京:清华大学出版社,1999
[12] 章毓晋.图像分割.北京:科学出版社,2001
[13] Erich Gamma,Richard Helm,Ralph Johnson,et al.设计模式:可复用面向对象软件的基础(李英军,马晓星,蔡敏等).北京:机械工业出版社,2000
[14] 贺俊吉,张广军.结构光三维视觉检测中光条图像处理方法研究.北京航空航天大学学报,2003,29(7):593～597
[15] 雷海军,李德华,王建永等.一种结构光条纹中心快速检测方法.华中科技大学学报(自然科学版),2003,31(1):74～76
[16] 王爱囡.粗糙表面散射光强分布的特征参数研究.合肥工业大学学报(自然科学版),2002,25(6):1249～1251
[17] 艾勇.最新光学应用测量技术.武汉:武汉测绘大学出版社,1994
[18] 陈青山,吕乃光,燕必希等.激光准直高斯光斑中心位置计算方法分析.计算机测量与控制,2004,12(15):486～488
[19] 隋连升,李兵,蒋庄德.基于NURBS曲线插值的激光光刀图像中心提取方法的研究.中国激光,2003,29(7):593～597
[20] 解则晓,张成国,张国雄.基于B样条迭代法的激光光条噪声去除技术研究.光学技术,2005,31(3):430～433
[21] Jim Beveridge,Robert Wiener.Win32多线程程序设计一线程完全手册(侯捷).武汉:华中科技大学出版社,2002
[22] 朱心雄.自由曲线曲面造型技术.北京:科学出版社,2000
[23]D onald Hearn, M. Pauline Baker.计算机图形学(蔡士杰,吴春镕,孙正兴等)北京: 电子工业出版社,2002
[24] 孙正兴,周良,郑宏源.计算机图形学基础教程.北京:清华大学出版社,2004
[25] 李胜瑞,王乘恩,王智高.计算机图形学试验教程(OpenGL版).北京:机械工业出版社,2004
[26] 尚游,张双,万磊等.OpenGL高级图形编程指南.哈尔滨:哈尔滨工程大学出版社,1999
[27] Eugene Olafsen,Kenn Scribner, K. David White,et al.MFC Visual C++6编程技术内幕(王建华,陈一飞,张焕生等).北京:机械工业出版社,2000
[28] Hu GongZhu, Gorge Stonman. 3D surface solution using structured light and constraint propagation. IEEE-PAMI, 1995, 11(4), 225～231
[29] A Rosenfeld, A C Kak. Digital Picture Processing. US: Academic Press, 1982
[30] Haralick R M, Shapiro I G, Image segmentation techniques. CVGIP, 1985, 29:100～132
[31] W Doyle. Operations useful for similarity-invariant pattern recognition. Journal of the ACM, 1962, 9(2): 259～267
[32] Deng Wenyi, Lu Naiguang, Zhuang Jingcheng, et al. A stereo vision system for measurement of 3D object. SPIE, 1998, 3558:248～525
[33] M A Sid-Ahmed, M T Boraie. Dual camera calibration for 3D machine vision. IEEE-Transaction on Instruction and Measurement, 1990, 39(4): 512～516
[34] Siriphan Jitprasithsiri. Development of a new digital pavement image processing algorithm for unified crack index computation: [PhD. thesis]. US: University of Utah, 1997
[35] Koutsopoulos H N, Downey A B. Primitive-based classification of pavement cracking images. Journal of Transportation Engineering, 1993, 119(3): 402～418
[36] Chou Jaching, O'Neill, Wende A, et al. Pavement distress evaluation using fuzzy logic and moment invariants. Transportation Research Record, 1995, 1505: 39～46
[37] Kaseko M S, Lo Z P, Ritchie S G. Comparison of Traditional and Neural Classifiers for Pavement Crack Detection. Journal of Transportation Engineering, ASCE, 1994, 120(4): 552～569.
[38] Cheng H D, Chen J R, Glazier C, et al. Novel approach to pavement cracking detection based on fuzzy set theory. Journal of Computing in Civil Engineering, 1999, 13(44): 270～280
[39] Cheng HengDa. Automated real-time pavement distress detection using fuzzy logic and neural network. SPIE Proceedings, 1996, 2946:140～151
[40] M Miyojim, H D Cheng. Novel System for Automatic Pavement Distress Detection. ASCE, 1998, 12(3): 145～152
[41] Horn B K P. Shape from shading: a method for obtaining the shape of a smooth opaque object from one view. MIT AI Laboratory Technical Report 232. Massachusetts: MIT, 1970
[42] ChunJung Hsu, ChiFarn Chen, Chao Lee, et al. Airport pavement distress image classification using moment invariant neural network. In: S C Lie weds, Proceedings of 22nd Asian Conference on Remote Sensing. Singapore: National University of Singapore, 2001, 216-220
[43] Milan Sonka, Valcav Hlavac, Roger Boyle. Image Processing, Analysis and Machine Vision (Photocopy). Beijing: Post and Telecom Press, 2002
[44] Sun Microsystems Inc. 1014. The Request for Comments. US: Internet Engineering Task Force and the Internet Engineering Steering Group, 1997
[45] M Eck, H Hoppe. Automatic reconstruction of B-spline surfaces of arbitrary topological type. Computer Graphics, 1996: 325-334
[46] H Hoppe, T DeRose, T Duchamp, et al. Surface reconstruction from unorganized points. Computer Graphics, 1992, 26(2): 71-78
[47] E Allgower, P Schmidt. An Algorithm for Piecewise-Linear Approximation of an Implicitly Defined Manifold. SIAM, Journal of Numerical Analysis, 1985,22(2): 322-346
[48] Charles Loop. Smooth subdivision surfaces based on triangles: [Master's thesis]. US: Department of Computer Science and Engineering, University of Washington, 1987
[49] H Hoppe, T DeRose, T Duchamp, et al. Mesh optimization. Computer Graphics (SIGGRAPH '93 Proceedings), 1993: 19-26
[50] Hugues Hoppe. Surface reconstruction from unorganized points: [PhD. thesis]. US: Department of Computer Science and Engineering, University of Washington, 1994
[51] Jackie Neider, Tom Davis. OpenGL Programming Guide. US: Addison-Wesley Publishing Company, 1997
[52] Dale Rogerson. OpenGL I: Quick Start. US: Microsoft Developer Network Technology Group, 1994