期刊文献+

高速公路多车道分道线快速检测与重建技术 被引量:9

Detection and reconstruction for multi-lane line on freeway
下载PDF
导出
摘要 介绍了基于单目视觉技术的高速公路多车道快速检测与重建技术,实现了高速公路的车道自动保持。采用双阈值法快速分割高速公路的白色分道线,用特征跟踪法提取分道线,根据道路视觉模型用圆锥曲线结合分道线特征点重建4条分道线。分析了根据道路视觉模型和分道线重建来实现车道保持的基本方法。该算法已经通过VC语言实现,系统在四川省和重庆市的高速公路上以最高120 km/h的速度进行了试验,圆满地完成了多车道检测任务,实现了车道保持。 Authors describe the multi-lane line detection and reconstruction with single view. At first, authors use double-threshold value method to extract the lane line, then, use feature point to track the lane line, at last, use the coned model to reconstruct the four lane lines. Authors also analyze the basic way to keep the road based on the vision model and the lane line model. Authors have experimented the system with the algorithms on freeway at 160 km/h in Sichuan province and Chongqing city in China. The result shows that the algorithms can work perfectly.
作者 周欣 黄席樾
出处 《中国公路学报》 EI CAS CSCD 北大核心 2005年第2期107-111,共5页 China Journal of Highway and Transport
基金 国家自然科学基金项目(69674012)
关键词 汽车运用工程 视觉导航 单目视觉技术 分道线检测 圆锥曲线模型 多车道重建 automobile application engineering vision navigation single view technology lane line detection coned model multi-lane line reconstruction
  • 相关文献

参考文献8

  • 1蒲浩,宋占峰,郑顺义,詹振炎.道路三维场景的实时动态显示技术[J].交通运输工程学报,2003,3(1):52-56. 被引量:32
  • 2AUFRERE R,CHAPUIS R,CHAUSSE F. A modeldriven approach for real-time road recognition[J]. Machine Vision and Application,2001,13(1): 95-107.
  • 3CHAPUIS R,AUFRERE R, CHAUSSE F. Accurate road following and reconstruction by computer vision[J]. IEEE Transactions on Intelligent Transportation Systems, 2002,3(4) :261-270.
  • 4KUAN D, PHIPPS G. Autonomous robotic vehicle road following[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1988,10(5): 648-658.
  • 5KANATANI K,WATANABE K. Reconstruction of 3-D road geometry from images for autonomous land vehicles[J]. IEEE Transactions on Robotics and Automation,1990,6(1):127-132.
  • 6GUIDUCCI A. Parametric model of the perspective projection of a road with applications to lane keeping and 3D road reconstruction[J]. Computer Vision and Image Understanding, 1999,73(3) :414-427.
  • 7廖传锦,柴毅,黄席樾.汽车防撞系统中目标跟踪与防撞决策研究[J].中国公路学报,2004,17(2):113-118. 被引量:6
  • 8许金良,杨宏志.公路视景仿真模型[J].长安大学学报(自然科学版),2004,24(2):37-40. 被引量:12

二级参考文献19

  • 1JANSSON J, JOHANSSON J. Decision making for collision avoidance system[A]. 2002 Society of Automotive Engineers [C]. Pennsylvania: World Headquarters, 2002.
  • 2MAURER M, BEHRINGER R, THOMANEK F,etc. A compact vision system for road vehicle guidance[A]. 13th Int. Conf. on Pattern Recognition (ICPR) [C]. Vienna: Technical University of Vienna,1996. 313 -317.
  • 3POMERLEAU D,JOCHEM T. Image processor drives across America[J]. Photonics Spectra, 1996, 11(2) :80-85.
  • 4POMERLEAU D,JOCHEM T. Rapidly adapting machine vision for automated vehicle steering[J]. IEEE Expert,1996, 11(2) :19-27.
  • 5PARAG H, BATAVIA. Driver-adaptive lane departure warning systems[D]. Pittsburgh: Camegie Mellon University, 1999.
  • 6BERTOZZI M, BROGGI A. GOLD: a parallel real time stereo vision system for generic obstacle and land detection[J]. IEEE Transaction on Image Processing, 1998,7 (1) :82-91.
  • 7BERTOZZI M, BROGGI A, FASCIOLI. ARGO and the millemiglia in automatic tour[J]. IEEE Intelligent System, 1999,14( 1 ): 55-64.
  • 8AMDITIS A, ANDREONE L, BEKIARIS A. Using aerospace technology to improve obstacle detection under adverse environmental conditions for car drivers[A]. The 1st International Conference on Univer sal Access in Human-Computer Interaction[C]. New Orleans:The
  • 9ANDREONE L,AMDITIS A,BEKIARIS A,etc. Fusion data from radar and IR sensors for enhancing automotive driver's vision under night and adverse weather conditions[EB/OL]. http:∥i-sense. iccs. ntua. gr/EuclideFusingData. pdf, 2003-12-22.
  • 10AMDITIS A,EVANGELOS B. Multiple-sensor-collision avoidance system for automotive applications using an IMM approach for obstacle tracking[A]. 5th International Conference on Information Fusion[C].Annapolis: IEEE Georgia Tech. Res. Inst., 2002.812-817.

共引文献42

同被引文献78

引证文献9

二级引证文献40

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部