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智能交通系统中的视频监控技术 被引量:4

Video Supervision Technique in Intelligent Traffic System
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摘要 介绍了在智能交通系统(ITS)中基于视频图像的车流量和车速检测、车辆类型检测和识别,以及车牌号码的定位和识别技术,并给出了应用实例。最后,结合目前的研究成果对视频图像在ITS中存在的问题和对未来的发展进行了展望。 The detection of the amount and speed of vehicles, detection and classification of vehicle types, and location and recognition of license plates based on video image in intelligent traffic system (ITS) are introduced. Then the applications of video image in ITS are given. Finally, the problems that still exist and the developmental trend of video image in ITS are discussed according to the latest progress.
作者 葛广英
出处 《电视技术》 北大核心 2006年第4期89-92,共4页 Video Engineering
基金 山东省科技攻关课题(022090107)
关键词 智能交通系统 视频图像 车辆检测 intelligent traffic system video image vehicle detection
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参考文献5

  • 1FANG yajun,MIZUKI M,MASAKI I,et al.TV camera-based vehicle motion detection and its chip implementation[C]//IEEE Intelligent Vehicles Symposium.Dearborn:Massachussetts Institute of Technology (USA),2000:134-139.
  • 2CUCCHIARA R,PICCARDI M,MELLO P.Image analysis and rule-based reasoning for a traffic monitoring system[J].IEEE Transactions on Intelligent Transportation Systems,2000,1(2):119-130.
  • 3GUPTE S,MASOUD O,PAPANIKOLOPOULOS N P.Visionbased vehicle classification [C]//2000 IEEE Intelligent Transportation Systems Conference Proceedings.Dearborn:[s.n.],2000:58-63.
  • 4LIPYON A J,FUJIYOSHI H,PATIL R.Moving target classification and tracking from real-time video [C]//.Proc.IEEE Workshop on Applications of Compnter Vision.Princeton:[s.n.],1998:8-14.
  • 5许锋,卢建刚,孙优贤.神经网络在图像处理中的应用[J].信息与控制,2003,32(4):344-351. 被引量:51

二级参考文献40

  • 1Lee C C, Degyves J P. Color image processing in a cellular neu-rid-network environment [ J ]. IEEE Transactions on Neural Networks, 1996,7(5) :1086 - 1098.
  • 2Clarke L P, Qian W. Fuzzy-logic adaptive neural networks for nuclear medicine image restoration [A]. The 20th Annual International Conference on Engineering in Medicine and Biology Society[C]. 1998,vol. 3. 1363 - 1366.
  • 3Qian W, Clarke L P. Wavelet-based neural network with fuzzylogic adaptivity for nuclear image restoration [J]. Proceedings of the IEEE, 1996,84(10) :1458 - 1473.
  • 4Cheung H N, Bouzerdoum A, Newland W. Properties of shunting inhibitory cellular neural networks for colour image enhancement[ A]. The 6th International Conference on Neural Information Processing [ C]. 1999 ,vol. 3. 1219 - 1223.
  • 5Kondo K, Iguch M, Ishigaki H, et al. Design of complex-valued CNN filters for medical image enhancement [ A ]. IFSA World Congress and 20th NAFIPS International Conference [C]. 2001,vol. 3.1642 - 1646.
  • 6Ahmed F, Gustafson S C, Karim M A. High-fidelity image interpolation using radial basia function neural networks [ A ]. Aerospace and Electronics Conference [ C ]. 1995,vol. 2. 588 -592.
  • 7Sun Y. Hopfield neural network based algorithms for image restoration and reconstruction I algorithms and simulations [ J ].IEEE Transactions on Signal Processing, 2000,48 ( 7 ) : 2105-2118.
  • 8Sun Y. Hopfield neural network based algorithms for image restoration and reconstruction II algorithms and simulations [ J ].IEEE Transactions on Signal Processing, 2000,48 ( 7 ) : 2105-2118.
  • 9Perry S W, Wyber R J. A Hopfield neural network approach for the reconstruction of wide-bandwidth sonar data. Neural Networks for Signal Processing, 2000,2:876 -885.
  • 10Dony R D, et al. Neural network approaches to image compression [J]. Proc IEEE, 1995,83:288 -303.

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