A real-time vision system for nighttime vehicle detection and traffic surveillance

IEEE Transactions on Industrial Electronics

Volumn 58, Issue 5, 2011, Pages 2030-2044

  Chen, Yen Lin ^a   Wu, Bing Fei ^b   Huang, Hao Yu ^b   Fan, Chung Jui ^c  

^a NATIONAL TAIPEI UNIVERSITY OF TECHNOLOGY   (Taiwan)

^b NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^c AU OPTRONICS CORPORATION   (Taiwan)

Author keywords

nighttime surveillance; Traffic information system; traffic surveillance; vehicle detection; vehicle tracking

Indexed keywords

NIGHTTIME SURVEILLANCE; TRAFFIC INFORMATION SYSTEM; TRAFFIC SURVEILLANCE; VEHICLE DETECTION; VEHICLE TRACKING;

HIGHWAY TRAFFIC CONTROL; IMAGE SEGMENTATION; INFORMATION SYSTEMS; MONITORING; VEHICLES;

TRACKING (POSITION);

EID: 79954524140     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2010.2055771     Document Type: Article

References (40)

1. V. Kastrinaki, M. Zervakis, and K. Kalaitzakis, "A survey of video processing techniques for traffic applications," Image Vis. Comput., vol. 21, no. 4, pp. 359-381, Apr. 2003.
2. W.-L. Hsu, H.-Y. , M. Liao, B.-S. Jeng, and K.-C. Fan, "Real-time traffic parameter extraction using entropy," Proc. Inst. Elect. Eng.-Vis. Image Signal Process., vol. 151, no. 3, pp. 194-202, Jun. 2004.
3. R. Cucchiara, M. Piccardi, and P. Mello, "Image analysis and rule-based reasoning for a traffic monitoring system," IEEE Trans. Intell. Transp. Syst., vol. 1, no. 2, pp. 119-130, Jun. 2000.
4. M.-C. Huang and S.-H. Yen, "A real-time and color-based computer vision for traffic monitoring system," in Proc. IEEE Int. Conf. Multimed. Expo, May 2004, pp. 2119-2122. (Pubitemid 40063483)
5. C. Stauffer and W. E. L. Grimson, "Adaptive background mixture models for real-time tracking," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., Jun. 1999, pp. 246-252.
6. J. Kong, Y. Zheng, Y. Lu, and B. Zhang, "A novel background extraction and updating algorithm for vehicle detection and tracking," in Proc. IEEE Int. Conf. Fuzz. Syst. Knowl. Discovery, 2007, pp. 464-468. (Pubitemid 351710941)
7. S. Gupte, O. Masoud, R. F. K. Martin, and N. P. Papanikolopoulos, "Detection and classification of vehicles," IEEE Trans. Intell. Transp. Syst., vol. 3, no. 1, pp. 37-47, Mar. 2002. (Pubitemid 135706831)
8. B.-F. Wu, S.-P. Lin, and Y.-H. Chen, "A real-time multiple-vehicle detection and tracking system with prior occlusion detection and resolution," in Proc. IEEE Int. Symp. Signal Process. Inf. Technol., Dec. 2005, pp. 311-316.
9. J. Zhou, D. Gao, and D. Zhang, "Moving vehicle detection for automatic traffic monitoring," IEEE Trans. Veh. Technol., vol. 56, no. 1, pp. 51-59, Jan. 2007. (Pubitemid 46358010)
10. W. F. Gardner and D. T. Lawton, "Interactive model-based vehicle tracking," IEEE Trans. Pattern Anal. Mach. Intell., vol. 18, no. 11, pp. 1115- 1121, Nov. 1996. (Pubitemid 126772847)
11. G. D. Sullivan, K. D. Baker, A. D. Worrall, C. I. Attwood, and P. M. Remagnino, "Model-based vehicle detection and classification using orthographic approximations," Image Vis. Comput., vol. 15, no. 8, pp. 649-654, Aug. 1997. (Pubitemid 127381941)
12. D. Koller, J. Weber, T. Huang, J. Malik, G. Ogasawara, B. Rao, and S. Russell, "Towards robust automatic traffic scene analysis in real-time," in Proc. Int. Conf. Pattern Recog., 1994, vol. 1, pp. 126-131.
13. N. Peterfreund, "Robust tracking of position and velocity with Kalman snakes," IEEE Trans. Pattern Anal. Mach. Intell., vol. 21, no. 6, pp. 564- 569, Jun. 1999.
14. S.-T. Tseng and K.-T. Song, "Real-time image tracking for traffic monitoring," in Proc. IEEE 5th Int. Conf. Intell. Transp. Syst., 2002, pp. 10-14.
15. L.-W. Tsai, J.-W. Hsieh, and K.-C. Fan, "Vehicle detection using normalized color and edge map," IEEE Trans. Image Process., vol. 16, no. 3, pp. 850-864, Mar. 2007. (Pubitemid 46431979)
16. D. Beymer, P. McLauchlan, B. Coifman, and J. Malik, "A real-time computer vision system for measuring traffic parameters," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., Jun. 1997, pp. 495-510.
17. K. Huang, L.Wang, T. Tan, and S.Maybank, "A real-time object detecting and tracking system for outdoor night surveillance," Pattern Recognit., vol. 41, no. 1, pp. 432-444, Jan. 2008. (Pubitemid 47284211)
18. M. Dufaut, R. Taktak, and R. Husson, "Vehicle detection at night using image processing and pattern recognition," in Proc. IEEE Int. Conf. Image Process., 1994, vol. 2, pp. 296-300.
19. R. Cucchiara and M. Piccardi, "Vehicle detection under day and night illumination," in Proc. 3rd Int. ICSC Symp. Intell. Ind. Autom. Soft Comput., 1999, pp. 1-4.
20. W. Wang, C. Shen, J. Zhang, and S. Paisitkriangkrai, "A two-layer nighttime vehicle detector," in Proc. Int. Conf. DICTA, 2009, pp. 619-626.
21. K. Robert, "Night-time traffic surveillance a robust framework for multivehicle detection, classification and tracking," in Proc. IEEE Conf. AVSS, 2009, pp. 1-6.
22. S. Tsugawa, "Vision-based vehicles in Japan: Machine vision systems and driving control systems," IEEE Trans. Ind. Electron., vol. 41, no. 4, pp. 398-405, Aug. 1994.
23. Z. Sun, G. Bebis, and R. Miller, "On-road vehicle detection: A review," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 5, pp. 694-711, May 2006.
24. Broggi, M. Bertozzi, A. Fascioli, and G. Conte, Automatic Vehicle Guidance: The Experience of the ARGO Autonomous Vehicle. Singapore: World Scientific, 1999.
25. H. Mori, M. Charkari, and T. Matsushita, "On-line vehicle and pedestrian detections based on sign pattern," IEEE Trans. Ind. Electron., vol. 41, no. 4, pp. 384-391, Aug. 1994.
26. A. Broggi, M. Cellario, P. Lombardi, and M. Porta, "An evolutionary approach to visual sensing for vehicle navigation," IEEE Trans. Ind. Electron., vol. 50, no. 1, pp. 18-29, Feb. 2003.
27. T. Bücher, C. Curio, J. Edelbrunner, C. Igel, D. Kastrup, I. Leefken, G. Lorenz, A. Steinhage, and W. Seelen, "Image processing and behavior planning for intelligent vehicles," IEEE Trans. Ind. Electron., vol. 50, no. 1, pp. 62-75, Feb. 2003.
28. B.-F. Wu, C.-T. Lin, and Y.-L. Chen, "Dynamic calibration and occlusion handling algorithms for lane tracking," IEEE Trans. Ind. Electron., vol. 56, no. 5, pp. 1757-1773, Apr. 2009.
29. M. Y. Chern and P. C. Hou, "The lane recognition and vehicle detection at night for a camera assisted car on highway," in Proc. IEEE Int. Conf. Robot. Autom., 2003, vol. 2, pp. 2110-2115.
30. C.-C.Wang, S.-S. Huang, and L.-C. Fu, "Driver assistance system for lane detection and vehicle recognition with night vision," in Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst., 2005, pp. 3530-3535.
31. Y.-L. Chen, Y.-H. Chen, C.-J. Chen, and B.-F. Wu, "Nighttime vehicle detection for driver assistance and autonomous vehicles," in Proc. 18th IAPR ICPR, 2006, vol. 1, pp. 687-690. (Pubitemid 46531995)
32. Y.-M. Chan, S.-S. Huang, L.-C. Fu, and P.-Y. Hsiao, "Vehicle detection under various lighting conditions by incorporating particle filter," in Proc. IEEE Intell. Transp. Syst. Conf., 2007, pp. 534-539.
33. A. M. López, J. Hilgenstock, A. Busse, R. Baldrich, F. Lumbreras, and J. Serrat, Nighttime Vehicle Detection for Intelligent Headlight Control, vol. 5259. Berlin, Germany: Springer-Verlag, 2008, ser. Lecture Notes in Computer Science, pp. 113-124.
34. P. G. Michalopoulos, "Vehicle detection video through image processing: The autoscope system," IEEE Trans. Veh. Technol., vol. 40, no. 1, pp. 21- 29, Feb. 1991.
35. M. Fathy and M. Y. Siyal, "A window-based image processing technique for quantitative and qualitative analysis of road traffic parameters," IEEE Trans. Veh. Technol., vol. 47, no. 4, pp. 1342-1349, Nov. 1998. (Pubitemid 128741261)
36. A. H. S. Lai and N. H. C. Yung, "Vehicle-type identification through automated virtual loop assignment and block-based direction-biased motion estimation," IEEE Trans. Intell. Transp. Syst., vol. 1, no. 2, pp. 86-97, Jun. 2000.
37. Y.-L. Chen, B.-F. Wu, and C.-J. Fan, "Real-time vision-based multiple vehicle detection and tracking for nighttime traffic surveillance," in Proc. IEEE Int. Conf. SMC, San Antonio, Texas, 2009, pp. 3452-3458.
38. B.-F. Wu, Y.-L. Chen, and C.-C. Chiu, "A discriminant analysis based recursive automatic thresholding approach for image segmentation," IEICE Trans. Inf. Syst., vol. E88-D, no. 7, pp. 1716-1723, Jul. 2005.
39. K. Suzuki, I. Horiba, and N. Sugie, "Linear-time connected-component labeling based on sequential local operations," Comput. Vis. Image Understand., vol. 89, no. 1, pp. 1-23, Jan. 2003.
40. P. Sneath and R. Sokal, Numerical Taxonomy. The Principle and Practice of Numerical Classification. New York: Freeman, 1973.