期刊文献+

基于机器视觉的道路上前方多车辆探测方法研究 被引量:11

A Study on Multiple Vehicle Detection Based on Computer Vision
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摘要 提出一种基于车辆特征的方法识别和跟踪前方的车辆。首先,利用车辆底部存在阴影的特征,在图像中确定可能存在的车辆区域。然后,通过分形维数计算该区域的纹理特征,排除非车辆区域。最后,利用车辆的边缘信息,通过投影变换方法,对候选区域内的车辆进行定位。此外,利用NM I特征法对定位的车辆进行确认。该算法对不同环境和光照条件下的车辆图片进行了测试,以及在高速公路上进行了实时跟踪试验,具有较好的鲁棒性和可靠性。 A front vehicle detection and tracking method based on vehicle feature is presented. First, the possible vehicle regions are obtained by detecting vehicle underneath shadow. Then, the non-vehicle regions are filtered from the area of interest by texture feature based on differential box counting. And the edge information of vehicle is used to position the vehicles by projection transformation. Finally, the positioned vehicles are verified based on normalized mutual information feature. The results of detection and tracking tests show that the method has good robustness and reliability.
出处 《汽车工程》 EI CSCD 北大核心 2006年第10期902-905,共4页 Automotive Engineering
关键词 计算机视觉 车辆探测 阴影和边缘 纹理特征 NMI特征法 Computer vision, Vehicle detection, Shadow and edge, Texture feature, NMI feature tech- nique
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参考文献10

  • 1Bensrhair A,Broggi A.Stereo Vision-based Feature Extraction for Vehicle Detection[C].IEEE Symposium on Intelligent Vehicles,France,June 2002.
  • 2Srinivasa N.A Vision-based Vehicle Detection and Tracking Method for Forward Collision Warning[C].IEEE Intelligent Vehicle Symposium,2002.
  • 3Margrit Betke.Multiple Vehicle Detection and Tracking in Hard Real-Time[C].IEEE Symposium on Intelligent Vehicles,France,June 2002.
  • 4周欣,黄席樾,樊友平,刘涛.汽车智能辅助驾驶系统中的单目视觉导航技术[J].机器人,2003,25(4):289-295. 被引量:24
  • 5李斌.[D].长春:吉林大学,2001.
  • 6Sun Zehang,Bebis George.On-road Vehicle Detection Using Gabor Filters and Support Vector Machines[C].International Conference on Digital Signal Processing,Greece,July 2002.
  • 7Bensrhair A,Broggi A.A Cooperative Approach to Vision-based Vehicle Detection[C].IEEE Intelligent Transportation Systems,2001.
  • 8Detlev N.Artificial Neural Networks in Real-time Car Detection and Tracking Applications[C].Pattern Recognition Letters,1996.
  • 9Chen Wen-Shiung,Yuan Shang-Yuan.Algorithms to Estimating Fractal Dimension of Textured Images[C].Image and Multidimensional Signal Processing Session,2001.
  • 10门蓬涛,张秀彬,张峰,孙志旻,吴炯.基于NMI特征的目标识别与跟踪[J].微计算机信息,2004,20(3):24-26. 被引量:16

二级参考文献21

  • 1Broggi A. Vision-based driving assistance[J]. IEEE Intelligent Systems, 1998, Nov/Dec, 22--23.
  • 2Murphy R R. Sensor and information fusion for improved visionbased vehicle guidance . IEEE Intelligent Systems, 1998,Nov/Dec, 49--56.
  • 3Franke U. Fast stereo based object detection for stop & go traffic . Proc 1996 IEEE Int' 1 Symp. Intelligent Vehicles .IEEE Press, 1996. 339--344.
  • 4Morizet-Mahoudeaux P. On-board and real-time expert control. IEEE Expert. Aug 1996. 71--81.
  • 5Thorpe C, Hebert M H. Vision and navigation for the carnegiemellonNavlab[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1988,10(3) : 362-- 373.
  • 6Turk M A, Morgenhaler D G. VITS-A vision system for autonomous land vehicle navigation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1988,10 (3) : 342-- 361.
  • 7Kuan D, Phipps G. Autonomous robotic vehicle road following. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1988,10(5) : 648-- 658.
  • 8Kanatani 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.
  • 9Guiducci A. Parametric model of the perspective projection of a road with applications to lane keeping and 3D road reconstruction. Computer Vision and Image Understanding, 1999,73 (3) :414--427.
  • 10Giachetti A, Campani M. The use of optical flow for road navigation. IEEE Transactions on Robotics and Automation, 1998,14(1) : 34--48.

共引文献44

同被引文献49

  • 1施树明,储江伟,李斌,郭烈,王荣本.基于单目视觉的前方车辆探测方法[J].农业机械学报,2004,35(4):5-8. 被引量:15
  • 2王荣本,张明恒,石德乐.双目视觉技术在目标测量中的应用[J].公路交通科技,2007,24(2):122-125. 被引量:22
  • 3Kunsoo Huh, Jaehak Park, Junyeon Hwang, et al. A Stereo Vision-based Obstacle Detection System in Vehicles[ J]. Optics and Lasers in Engineering, 2008,46 ( 2 ) : 168 - 178.
  • 4Yong Chen, Xia Liu, Qi Huang. Real-time Detection of Rapid Moving Infrared Target on Variation Background [ J ]. Infrared Physics & Technology, 2008,51 ( 3 ) : 146 - 151.
  • 5Zhen Jia, Arjuna Balasuriya. Vision Based Data Fusion for Autonomous Vehicles Target Tracking Using Interacting Multiple Dynamic Models[ J ]. Computer Vision and Image Understanding,2008, 109(1):1 -21.
  • 6Sun Zehang, Bebis George. On-road Vehicle Detection Using Gabor Filters and Support Vector Machines[ C ]. International Conference on Digital Signal Processing, Greece, July 2002.
  • 7Sun Zehang, Bebis G, Miller R. On-road vehicle detection :A review[ J]. IEEE Transactions on Pattern Anahsis and Machine Intelligence, 2006,28 ( 5 ) : 694 - 711.
  • 8Yoi Chiro lwasaki, Yuji Kurogi. Real-time robust vehicle detection through the same algorithm both day and night [ C ]//Proceeding of the 2007 International Conference on Wavelet Analysisand Pattern Recognition. Beiiing:[s. n. ].2007:1008 - 1014.
  • 9Margit Betke, Esin Haritaoglu, Davis L S. Multiple vehicle detection and tracking in hard real time [ C ]//IEEE Symposium on Intelligent Vehicles. France: [ s. n. ] ,2002.
  • 10谢风英,赵丹培.Visual C++数字图像处理[M].北京:电子工业出版社,2008:285-288.

引证文献11

二级引证文献36

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