Review on Image Processing Based Vehicle Detection & Tracking System
Keywords:
Vehicle Detection, Tracking, Traffic Surveillance, Occlusion, Shadow & Classification.Abstract
The difficulty of obtaining the initial background there is the inaccuracy of real-time background update and the difficulty of controlling the update speed in moving vehicle detection of traffic video. The project aim proposes an accurate and effective moving vehicle detection method which can be used in complex traffic environment. Vehicle detection and tracking system plays an important role for civilian and military applications such as in highway traffic surveillance control, management and urban traffic planning. Vehicle detection process on road are used for vehicle tracking, counts the vehicle, average speed of each individual vehicle, traffic analysis and vehicle categorizing objectives and may be implemented under different environments changes. In this review, we present a concise overview of image processing methods and analysis tools which used in building these previous mentioned applications that involved developing traffic surveillance systems. More precisely and in contrast with other reviews, we classified the processing methods under three categories for more clarification to explain the traffic system.
References
- H. Chung-Lin and L. Wen-Chieh, "A vision-based vehicle identification system," in Pattern
- Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 2004, pp. 364-367 Vol.4. Z. Wei, et al., "Multilevel Framework to Detect and Handle Vehicle Occlusion," Intelligent Transportation Systems, IEEE Transactions on, vol. 9, pp. 161-174, 2008.
- N. K. Kanhere and S. T. Birchfield, "Real-Time Incremental Segmentation and Tracking of Vehiclesat Low Camera Angles Using Stable Features," Intelligent Transportation Systems, IEEETransactions on, vol. 9, pp. 148-160, 2008.
- N. K. Kanhere, "Vision-based detection, tracking and classification of vehicles using stable featureswith automatic camera calibration," ed, 2008, p. 105
- W. Wei, et al., "A method of vehicle classification using models and neural networks," in VehicularTechnology Conference, 2001. VTC 2001 Spring. IEEE VTS 53rd, 2001, pp. 3022-3026 vol.4.
- K. H. Lim, et al., "Lane-Vehicle Detection and Tracking," Proceedings of the International Multi-Conference of Engineers and Computer Scientists (IMECS 2009), vol. 2, pp. 5?10, 2009.
- M. Betke and H. Nguyen, “Highway scene analysis from a moving vehicle under deduced visibility conditions”, in Proc. IEEE Intell. Vehicle, 1998, pp. 131-136.
- R. Cucchiara, M. Piccardi, P. Mello, “Image analysis and rule-based reasoning for a traffic monitoring system”, IEEE Trans. On Intell. Transport. Syst., vol 1. No.2, June 2000.
- DAI Ke-xue, LI Guo-hui, TU Dan, YUAN Jian. “Prospects and Current Studies on Background Subtraction Techniques for Moving Objects Detection from Surveillance Video”. Journal of Image and Graphics. 2006, Vol.11, pp.919-927.
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