一种实时在线的公路路面破损及位置检测装置
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摘要
提出一种实时在线的公路路面破损及位置检测装置,该装置采用图像处理识别技术判定采集的路面图像是否存在破损,应用北斗导航系统进行破损定位,并通过移动通信系统实现破损图片和位置信息的实时传输,整个装置采用FPGA加以实现。在路面破损识别中,改进了Sobel算法,进一步提高了检测的准确性和抗干扰能力。以裂缝识别为例,将裂缝分为横向、纵向、块状和龟裂四类,该装置在车速70 km/h下,识别准确性可达到88.75%。此外,整个系统管理后台显示破损图片、破损类型、位置和地图标注等信息。
A real-time on-line road pavement breakage and position detection device is proposed in this essay. The device uses image processing identification technology to determine whether there is any damage in the acquired images of road surface. The Beidou navigation system is applied to locate the damaged object while the mobile communication system is used to realize the re-al-time transmission of damaged images and the information of location. The entire device can be achieved through using FPGA.In the identification of pavement damage, Sobel algorithm is improved, which could further increase the accuracy of detection and enhance the ability of anti-interference. Illustrated by the example of crack identification, the cracks are divided into four categories :lateral, longitudinal, block and crack. The accuracy of this device can reach 88. 75 % under the speed of 70 km/h. In addition,the background of the entire system administration displays the information of broken images, broken types, location, map annotations and so on.
A real-time on-line road pavement breakage and position detection device is proposed in this essay. The device uses image processing identification technology to determine whether there is any damage in the acquired images of road surface. The Beidou navigation system is applied to locate the damaged object while the mobile communication system is used to realize the re-al-time transmission of damaged images and the information of location. The entire device can be achieved through using FPGA.In the identification of pavement damage, Sobel algorithm is improved, which could further increase the accuracy of detection and enhance the ability of anti-interference. Illustrated by the example of crack identification, the cracks are divided into four categories :lateral, longitudinal, block and crack. The accuracy of this device can reach 88. 75 % under the speed of 70 km/h. In addition,the background of the entire system administration displays the information of broken images, broken types, location, map annotations and so on.
引文
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[16]闫建巧,陈明剑,汪威,等.基于地基增强系统的增强PPP技术[J].全球定位系统,2016,41(2):50-54.
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[18]陈娟,文振宇,李志强,等.一种快速手势识别算法的实现与验证[J].实验科学与技术,2011,9(6):34-36.
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[20]李鹏,杜敏,赵芬芬.基于FPGA图像分析的路面破损检测系统的研究与实现[J].微电子学与计算机,2017,34(3):100-104.
[21]刘博峰,郜丽鹏.基于FPGA的Sobel图像边缘检测算法[J].应用科技,2016,43(6):59-61.
[22]张建军,罗静.基于改进Sobel算子的表面裂纹边缘检测算法[J].合肥工业大学学报(自然科学版),2011,34(6):845-848.
[2]COUNCIL N.Automated imaging technologies for pavement distress surveys[C].Transportation Research E-Circular,2011.
[3]KLASSEN G,SWINDALL B.Automated crack detection system implementation in ARAN[C].Digital Image Processing:Techniques and Applications in Civil Engineering,1993.
[4]LAURENT J,LEFEBVRE D,SAMSON E.Development of a new 3D transverse laser profiling system for the automatic measurement of road cracks[J].Symposium on Pavement Surface Characteristics Portoroz Slovenia,2008.
[5]赵春霞,唐振民,杨静宇,等.N-1型道路状况智能检测系统[C].中国人工智能学会全国学术年会,2003.
[6]武汉武大卓越科技有限责任公司,道路检测[EB/OL].(2016-04-03).http://www.zoyon.com.cn/index.php/indexshow-tid-31.html.
[7]王建锋.激光路面三维检测专用车技术与理论研究[D].西安:长安大学,2010.
[8]American Association of State Highway and Transportation Officials(AASHTO)Guide for Design of Pavement Structures[M].Washington,D.C.,2002.
[9]张杰.基于FPGA的数字图像处理[D].武汉:华中科技大学,2009.
[10]孟显英.中值滤波算法的FPGA设计与实现[J].电脑知识与技术,2010,27(6):7822-7824.
[11]何春华,张雪飞,胡迎春.基于改进Sobel算子的边缘检测算法的研究[J].光学技术,2012,38(3):332-337.
[12]KELVIN C,WANG P.Elements of automated survey of pavements and a 3D methodology[J].Journal of Modern Transportation,2011,19(1):51-57.
[13]宋俊芳.路面检测关键技术综述[J].科教导刊,2016(18):156-157.
[14]李亚鹏,马润.基于北斗卫星的电力调度应急通信系统的研究[J].宁夏电力,2015(2):51-55.
[15]刘天恒,陈明剑,张树为,等.北斗地基增强系统数据通信综述[J].全球定位系统,2017,42(1):65-69.
[16]闫建巧,陈明剑,汪威,等.基于地基增强系统的增强PPP技术[J].全球定位系统,2016,41(2):50-54.
[17]刘天恒,陈明剑,尹子明,等.基于北斗地基增强系统RTD精度分析[C].中国卫星导航学术年会,2016.
[18]陈娟,文振宇,李志强,等.一种快速手势识别算法的实现与验证[J].实验科学与技术,2011,9(6):34-36.
[19]卢春雨,张长水,闻方,等.基于区域特征的快速人脸检测法[J].清华大学学报(自然科学版),1999,39(1):101-105.
[20]李鹏,杜敏,赵芬芬.基于FPGA图像分析的路面破损检测系统的研究与实现[J].微电子学与计算机,2017,34(3):100-104.
[21]刘博峰,郜丽鹏.基于FPGA的Sobel图像边缘检测算法[J].应用科技,2016,43(6):59-61.
[22]张建军,罗静.基于改进Sobel算子的表面裂纹边缘检测算法[J].合肥工业大学学报(自然科学版),2011,34(6):845-848.