Crossing road monitoring system based on adaptive decision for illegal situation

Automatically detecting and tracking crossing lane line vehicles in the illegal situation is an important part of E-police system. However, till now, there is few research works reported for it. In this paper, a novel crossing road monitoring system containing two cameras is built, which is composed of several steps. The long-range camera is used for lane lines extraction by improved multiple Hough transforms, and illegal vehicle is detected according to the distance between vehicle center and lane lines. Then, the illegal vehicle is tracked and license plate is captured by the close-range camera. The records used for police checking contain the video of illegal process and license plate. The proposed system has been used by the traffic administration bureau. The results on actual application show that this novel system can be used for E-police with high detection accuracy.

[1]  Fenghui Yao,et al.  Multiple moving target detection, tracking, and recognition from a moving observer , 2008, 2008 International Conference on Information and Automation.

[2]  Michael Greenspan,et al.  Efficient tracking with the Bounded Hough Transform , 2004, CVPR 2004.

[3]  Charles E. Thorpe,et al.  SCARF: a color vision system that tracks roads and intersections , 1993, IEEE Trans. Robotics Autom..

[4]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[5]  R. Benosman,et al.  A volumetric multi-cameras method dedicated to road traffic monitoring , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[6]  Joan Serrat,et al.  Robust Lane Lines Detection and Quantitative Assessment , 2007, IbPRIA.

[7]  Larry S. Davis,et al.  Efficient mean-shift tracking via a new similarity measure , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[8]  Yo-Sung Ho,et al.  Traffic parameter extraction using video-based vehicle tracking , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[9]  Franz J. Meyer,et al.  Traffic monitoring with spaceborne SAR - Theory, simulations, and experiments , 2007, Comput. Vis. Image Underst..

[10]  Hsu-Yung Cheng,et al.  Lane Detection With Moving Vehicles in the Traffic Scenes , 2006, IEEE Transactions on Intelligent Transportation Systems.

[11]  Gao Tao,et al.  Redundant discrete wavelet transforms based moving object recognition and tracking , 2009 .

[12]  Suchendra M. Bhandarkar,et al.  Fast and Robust Background Updating for Real-time Traffic Surveillance and Monitoring , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[13]  Jitendra Malik,et al.  Object detection using a max-margin Hough transform , 2009, CVPR.

[14]  ZuWhan Kim,et al.  Robust Lane Detection and Tracking in Challenging Scenarios , 2008, IEEE Transactions on Intelligent Transportation Systems.

[15]  Luis Salgado,et al.  Robust multiple lane road modeling based on perspective analysis , 2008, 2008 15th IEEE International Conference on Image Processing.

[16]  Jitendra Malik,et al.  A real-time computer vision system for measuring traffic parameters , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[17]  Jang Myung Lee,et al.  Applications of moving windows technique to autonomous vehicle navigation , 2006, Image Vis. Comput..

[18]  Zhidong Li,et al.  An improved mean-shift tracker with kernel prediction and scale optimisation targeting for low-frame-rate video tracking , 2008, 2008 19th International Conference on Pattern Recognition.

[19]  Bang Jun Lei,et al.  Real-time outdoor video surveillance with robust foreground extraction and object tracking via multi-state transition management , 2006, Pattern Recognit. Lett..

[20]  Fernando Jaureguizar Núñez,et al.  Robust Multiple Lane Road Modeling Based on Perspective Analysis , 2008, ICIP 2008.

[21]  Charles E. Thorpe,et al.  Vision-based neural network road and intersection detection and traversal , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[22]  Mohan M. Trivedi,et al.  Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation , 2006, IEEE Transactions on Intelligent Transportation Systems.

[23]  Kai-Tai Song,et al.  Real-time image tracking for automatic traffic monitoring and enforcement applications , 2004, Image Vis. Comput..

[24]  Dean A. Pomerleau,et al.  Visibility estimation from a moving vehicle using the RALPH vision system , 1997, Proceedings of Conference on Intelligent Transportation Systems.