沥青路面车辙深度检测系统研究
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摘要
随着我国沥青公路建设的飞速发展，沥青公路在公路总里程中所占的比例越来越大，沥青公路建成后的管理与养护工作也需要快速的跟进；由于沥青公路使用年限为10年，我国早期的沥青公路已出现破损情况。车辙是沥青公路主要病害之一，破坏路面，危害行车安全。因此，如何对庞大的沥青公路资源进行快速、客观、准确的检测，对我国沥青公路工程施工质量评价及养护管理具有重要意义。
本文主要对沥青路面车辙深度检测系统进行研究。针对目前沥青路面车辙检测系统的关键问题，根据系统的主要功能和技术指标，在国内外先进技术的基础之上，选择合适的检测方法，提出解决关键问题的方案。
本文主要完成以下3方面工作：
(1)研究国内外检测技术现状，结合检测系统的主要功能和技术指标，综合国内外的先进技术，选择合适的检测方案，采用基于线结构光的主动视觉法为检测方案，结合图像处理技术，实现对沥青路面进行无接触、无破损、高速度和高精度检测。；
(2)针对实际的路面检测环境，选择合适的CCD摄像机及图像采集卡，并与特定的工控机平台相结合，组成图像分析系统的主要硬件环境，选取有效的路面图像算法完成路面图像的处理工作；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。
(3)对沥青路面的车辙评价进行了分析。从行车安全的角度，对现有车辙各评价指标进行了讨论，并提出了新的评价指标设想，对新指标进行了初步探讨，各评价指标的确可以描述车辙的不同特点。
With the rapid development of national asphalt highway construction, the occupancy which asphalt highway possess at highway overall mileage is larger and larger. It is necessary to develop the maintained job immediately after asphalt highway has constructed. Because of the asphalt highway can only serve 10 years, the asphalt highway which has been constructed early has damaged in our country. Rut is one of the primary damage of the asphalt highway, it imperil the pavement and compromise the security of driving. Therefore, how to make the precise, impersonal and fast detection with enormous asphalt highway resources is supposed to be significant to the appraisement on the construction and maintenance on national asphalt highway.
In this dissertation, focuses on the depth of rut in asphalt pavement surface detection system. In view of existence key problem of the depth of rut in asphalt pavement surface detection system and main function and the technical specification, studying the domestic and foreign advance technology, selecting the method of detection, proposing the solution to key problem.
In this dissertation has solved three questions.
Firstly, investigating present situation of the domestic and foreign technology, incorporate with main function and the technology, selecting the method of solution. It takes initiative visual technology which based on linear laser as the scheme of the detection, makes the detection without touch, damage and in rapidly, high precision.
Secondly, in view of actual environment of detection, selecting proper CCD camera and image collection card, combining it with industry computer, composing main hardware of image analyze system, designing effective image algorithm for the system. 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.
Finally, analyze appraise parameters of the rut. From aspect of driving security, discussing the present appraise parameters, supposing new parameters to describe different characteristic of rut.
本文主要对沥青路面车辙深度检测系统进行研究。针对目前沥青路面车辙检测系统的关键问题，根据系统的主要功能和技术指标，在国内外先进技术的基础之上，选择合适的检测方法，提出解决关键问题的方案。
本文主要完成以下3方面工作：
(1)研究国内外检测技术现状，结合检测系统的主要功能和技术指标，综合国内外的先进技术，选择合适的检测方案，采用基于线结构光的主动视觉法为检测方案，结合图像处理技术，实现对沥青路面进行无接触、无破损、高速度和高精度检测。；
(2)针对实际的路面检测环境，选择合适的CCD摄像机及图像采集卡，并与特定的工控机平台相结合，组成图像分析系统的主要硬件环境，选取有效的路面图像算法完成路面图像的处理工作；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。
(3)对沥青路面的车辙评价进行了分析。从行车安全的角度，对现有车辙各评价指标进行了讨论，并提出了新的评价指标设想，对新指标进行了初步探讨，各评价指标的确可以描述车辙的不同特点。
With the rapid development of national asphalt highway construction, the occupancy which asphalt highway possess at highway overall mileage is larger and larger. It is necessary to develop the maintained job immediately after asphalt highway has constructed. Because of the asphalt highway can only serve 10 years, the asphalt highway which has been constructed early has damaged in our country. Rut is one of the primary damage of the asphalt highway, it imperil the pavement and compromise the security of driving. Therefore, how to make the precise, impersonal and fast detection with enormous asphalt highway resources is supposed to be significant to the appraisement on the construction and maintenance on national asphalt highway.
In this dissertation, focuses on the depth of rut in asphalt pavement surface detection system. In view of existence key problem of the depth of rut in asphalt pavement surface detection system and main function and the technical specification, studying the domestic and foreign advance technology, selecting the method of detection, proposing the solution to key problem.
In this dissertation has solved three questions.
Firstly, investigating present situation of the domestic and foreign technology, incorporate with main function and the technology, selecting the method of solution. It takes initiative visual technology which based on linear laser as the scheme of the detection, makes the detection without touch, damage and in rapidly, high precision.
Secondly, in view of actual environment of detection, selecting proper CCD camera and image collection card, combining it with industry computer, composing main hardware of image analyze system, designing effective image algorithm for the system. 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.
Finally, analyze appraise parameters of the rut. From aspect of driving security, discussing the present appraise parameters, supposing new parameters to describe different characteristic of rut.
引文
[1] 黄颂昌，徐剑，秦永春．我国沥青路面养护技术现状与发展展望．公路交通科技．2006，8：5～7
[2] 马建，宋宏勋．高速质量激光检公路养护测技术及应用．筑路机械与施工机械化．2005，6：1～4
[3] 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
[4] 尤占平。沥青路面车辙及其评价．云南交通科技．1999，12，15(6)：22～44
[5] 梁新政，潘卫育，徐宏．路面无损检测技术新发展．公路。2002，9：95～98
[6] 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
[7] Siriphan Jitprasithsiri. Development of a new digital pavement image processing algorithm for unified crack index computation: [PhD. thesis]. US: University of Utah, 1997
[8] Koutsopoulos H N, Downey A B. Primitive-based classification of pavement cracking images. Journal of Transportation Engineering, 1993, 119(3): 402～418
[9] Chou Jaching, O'Neill, Wende A, et al. Pavement distress evaluation using fuzzy logic and moment invariants. Transportation Research Record, 1995, 1505: 39～46
[10] 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.
[11] 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
[12] 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
[13] M Miyojim, H D Cheng. Novel System for Automatic Pavement Distress Detection. ASCE, 1998, 12(3): 145～152
[14] 王晓嘉，高隽，王磊．激光三角法综述．仪器仪表学报．2004，8：601～604
[15] 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
[16] Hom 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
[17] 章毓晋．图像工程：图像处理和分析．北京：清华大学出版社，1999
[18] 章毓晋．图像分割．北京：科学出版社，2001
[19] 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
[20] 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
[21] 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
[22] Deng Wenyi, Lu Naiguang, Zhuang Jingcheng, et al. A stereo vision system for measurement of 3D object. SPIE, 1998, 3558:248～525
[23] 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
[24] 华艳秋．沥青路面行车性能检测摄像机标定技术研究：[硕士学位论文]．武汉：武汉理工大学，2006
[25] 艾勇．最新光学应用测量技术．武汉：武汉测绘大学出版社，1994
[26] 乌秀春．反求工程中基于图像灰度信息的三维曲面重构研究[博士学位论文]．大连：大连理工大学，2002
[27] 杨峻，倪嘉陵．现代测量方法在逆求工程中的应用．武汉汽车工业大学学报．1998,20(31：23～26
[28] Wu Xiaofeng, Zhang Guoxiong. Development of a modem coordinate measuring machine, Nanotechnology and Precision Engineering,2006,4(4): 301～307
[29] 邓劲莲，屠立，王循明．基于三坐标测量机的曲面轮廓反向工程数字化测量方法．2006,23(6)：22～25
[30] 艾勇．最新光学应用测量技术．武汉：武汉测绘大学出版社，1994
[31] M.Ishii, T. Nagata, Feature extraction of three-dimensional object and processingin hand-eye' system using laser tracker[J]. Pattern Recognition, 1976, VolB, No.4,p229～237
[32] 熊汉伟，张湘伟．由单幅图像重构表面形状的B样条变分法研究．计算机辅助设计与图形学学报．2001，2(13)：111～117
[33] 廖熠，赵荣椿．从明暗恢复形状方法综述．中国图像图形学报．2001，6(10)：953～961
[34] 解则晓，张成国，张国雄。线结构光测头的误差补偿。仪器仪表学报．2005,26(7)：667～670
[35] 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
[36] 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
[37] R.A. Jarvis, a Perspective on Range Finding Techniques for Computer Vision[J],IEEE Trans. On PA&MI, March,1983, VoI.PAMI-5, No.2, p122～139
[38] O.Ozeki, etc, Real time range measurement device for 3D object recognition[J].IEEE Trans. PA&MI, 1986,vol.8, No.S, p550-533
[39] M. Atiquzzaman.Coarse-to-Fine Search Technique to Detect Circles in Images.Int J Adv Manuf Technol. 1999.(15): 96-102
[40] Rosenfeld A, Torre P. Histogram concavity analysis as an aid in threshold selection.IEEE Systems, Man and Cybernetics, 1983.(13): 231-235
[41] Brian Curless, From Range Scans to 3D models[J], Appears in Computer Graphics, 1999,Vol 33, No 4, 38-41
[42] 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
[43] Zhang T Y, Suen C Y.A fast parallel algorithm for thinning digital patterns.Communication of Association for Computing Machinery, 1984.(27): 236-239
[44] M. Atiquzzaman.Coarse-to-Fine Search Technique to Detect Circles in Images.hat J Adv Manuf Technol. 1999.(15): 96-102
[45] 夏云庆．Visual C++6.0数据库高级编程．北京：希望电子出版社，2002
[46] 成功，杨佃福．VC中几种数据库访问技术的比较与选择．计算机应用研究．2002,2：82～84
[47] Takashi M. A survey of image processing and computer vision software systems on workstation.International Association for Pattern Recognition.TOC5, 1992.1-35
[48] 张家精，倪友聪．DAO技术在数据库访问中的应用与实现．计算机与现代化．2006,12：46～48
[49] 刘艳丽，黄俊，熊吉春．利用DAO实现VisualC++对数据库的访问．信阳师范学院学报(自然科学版)．2000,1(13)：71～75
[50] IA-32 Intel Architecture Software Developer's Manual [M].2001
[51] 张静．沥青混合料温度稳定性与路面设计。西安：长安大学道路工程系，2001，(6)：70-71
[52] 沈金安．沥青及沥青混合料路用性能．北京：人民交通出版社，2001：349～350
[53] SHRP-A-415.Pavement Deformation Response of Asphalt Aggregate Mixes.N.C.R.uSA, 1994,(5): 215-216
[2] 马建，宋宏勋．高速质量激光检公路养护测技术及应用．筑路机械与施工机械化．2005，6：1～4
[3] 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
[4] 尤占平。沥青路面车辙及其评价．云南交通科技．1999，12，15(6)：22～44
[5] 梁新政，潘卫育，徐宏．路面无损检测技术新发展．公路。2002，9：95～98
[6] 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
[7] Siriphan Jitprasithsiri. Development of a new digital pavement image processing algorithm for unified crack index computation: [PhD. thesis]. US: University of Utah, 1997
[8] Koutsopoulos H N, Downey A B. Primitive-based classification of pavement cracking images. Journal of Transportation Engineering, 1993, 119(3): 402～418
[9] Chou Jaching, O'Neill, Wende A, et al. Pavement distress evaluation using fuzzy logic and moment invariants. Transportation Research Record, 1995, 1505: 39～46
[10] 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.
[11] 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
[12] 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
[13] M Miyojim, H D Cheng. Novel System for Automatic Pavement Distress Detection. ASCE, 1998, 12(3): 145～152
[14] 王晓嘉，高隽，王磊．激光三角法综述．仪器仪表学报．2004，8：601～604
[15] 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
[16] Hom 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
[17] 章毓晋．图像工程：图像处理和分析．北京：清华大学出版社，1999
[18] 章毓晋．图像分割．北京：科学出版社，2001
[19] 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
[20] 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
[21] 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
[22] Deng Wenyi, Lu Naiguang, Zhuang Jingcheng, et al. A stereo vision system for measurement of 3D object. SPIE, 1998, 3558:248～525
[23] 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
[24] 华艳秋．沥青路面行车性能检测摄像机标定技术研究：[硕士学位论文]．武汉：武汉理工大学，2006
[25] 艾勇．最新光学应用测量技术．武汉：武汉测绘大学出版社，1994
[26] 乌秀春．反求工程中基于图像灰度信息的三维曲面重构研究[博士学位论文]．大连：大连理工大学，2002
[27] 杨峻，倪嘉陵．现代测量方法在逆求工程中的应用．武汉汽车工业大学学报．1998,20(31：23～26
[28] Wu Xiaofeng, Zhang Guoxiong. Development of a modem coordinate measuring machine, Nanotechnology and Precision Engineering,2006,4(4): 301～307
[29] 邓劲莲，屠立，王循明．基于三坐标测量机的曲面轮廓反向工程数字化测量方法．2006,23(6)：22～25
[30] 艾勇．最新光学应用测量技术．武汉：武汉测绘大学出版社，1994
[31] M.Ishii, T. Nagata, Feature extraction of three-dimensional object and processingin hand-eye' system using laser tracker[J]. Pattern Recognition, 1976, VolB, No.4,p229～237
[32] 熊汉伟，张湘伟．由单幅图像重构表面形状的B样条变分法研究．计算机辅助设计与图形学学报．2001，2(13)：111～117
[33] 廖熠，赵荣椿．从明暗恢复形状方法综述．中国图像图形学报．2001，6(10)：953～961
[34] 解则晓，张成国，张国雄。线结构光测头的误差补偿。仪器仪表学报．2005,26(7)：667～670
[35] 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
[36] 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
[37] R.A. Jarvis, a Perspective on Range Finding Techniques for Computer Vision[J],IEEE Trans. On PA&MI, March,1983, VoI.PAMI-5, No.2, p122～139
[38] O.Ozeki, etc, Real time range measurement device for 3D object recognition[J].IEEE Trans. PA&MI, 1986,vol.8, No.S, p550-533
[39] M. Atiquzzaman.Coarse-to-Fine Search Technique to Detect Circles in Images.Int J Adv Manuf Technol. 1999.(15): 96-102
[40] Rosenfeld A, Torre P. Histogram concavity analysis as an aid in threshold selection.IEEE Systems, Man and Cybernetics, 1983.(13): 231-235
[41] Brian Curless, From Range Scans to 3D models[J], Appears in Computer Graphics, 1999,Vol 33, No 4, 38-41
[42] 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
[43] Zhang T Y, Suen C Y.A fast parallel algorithm for thinning digital patterns.Communication of Association for Computing Machinery, 1984.(27): 236-239
[44] M. Atiquzzaman.Coarse-to-Fine Search Technique to Detect Circles in Images.hat J Adv Manuf Technol. 1999.(15): 96-102
[45] 夏云庆．Visual C++6.0数据库高级编程．北京：希望电子出版社，2002
[46] 成功，杨佃福．VC中几种数据库访问技术的比较与选择．计算机应用研究．2002,2：82～84
[47] Takashi M. A survey of image processing and computer vision software systems on workstation.International Association for Pattern Recognition.TOC5, 1992.1-35
[48] 张家精，倪友聪．DAO技术在数据库访问中的应用与实现．计算机与现代化．2006,12：46～48
[49] 刘艳丽，黄俊，熊吉春．利用DAO实现VisualC++对数据库的访问．信阳师范学院学报(自然科学版)．2000,1(13)：71～75
[50] IA-32 Intel Architecture Software Developer's Manual [M].2001
[51] 张静．沥青混合料温度稳定性与路面设计。西安：长安大学道路工程系，2001，(6)：70-71
[52] 沈金安．沥青及沥青混合料路用性能．北京：人民交通出版社，2001：349～350
[53] SHRP-A-415.Pavement Deformation Response of Asphalt Aggregate Mixes.N.C.R.uSA, 1994,(5): 215-216