Robust and Real-Time Traffic Lights Recognition in Complex Urban Environments

International Journal of Computational Intelligence Systems

Volumn 4, Issue 6, 2011, Pages 1383-1390

  Wang, Chunxiang ^a   Jin, Tao ^a   Yang, Ming ^b   Wang, Bing ^b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b Department of Automation   (China)

Author keywords

Candidate regions filtering; Color threshold segmentation; Image processing; Pattern recognition; Template matching; Traffic lights recognition

Indexed keywords

AUTOMATIC SYSTEMS; NOISE REMOVAL; NORMALIZED CROSS CORRELATION; REAL TIME TRAFFICS; REAL-TIME DETECTION; SHAPE INFORMATION; THRESHOLD SEGMENTATION; TRAFFIC LIGHT; URBAN ENVIRONMENTS; URBAN ROAD;

ALGORITHMS; IMAGE PROCESSING; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; PATTERN RECOGNITION; TEMPLATE MATCHING;

URBAN PLANNING;

EID: 84860867208     PISSN: 18756891     EISSN: 18756883     Source Type: Journal    
DOI: 10.1080/18756891.2011.9727889     Document Type: Article

References (21)

1. Wang, W., Hou, F. and Tan, H. 2010. A Framework for Function Allocation in Intelligent Driver Interface Design for Comfort and Safety. International Journal of Computational Intelligence Systems, 3(5): 531-541.
2. Wang, W., Guo, H. and Ikeuchi, K. 2011. Numerical simulation and analysis procedure for digital driving dependability in intelligent transport system. KSCE Journal of Civil Engineering, 15(5): 891-898.
3. Wang, W., Mao, Y. and Jing, J. 2011. Driver's various information process and multi-ruled decision-making mechanism: a fundamental of intelligent driving shaping model. International Journal of Computational Intelligence Systems, 4(3): 297-305.
4. Hwang, T., Joo, I. and Cho, S. 2006. "Detection of traffic lights for vision-based car navigation systems". In Pacific-Rim Symposium on Image and Video Technology 682-691.
5. Escalera, A., Armingol, J. and Mata, M. 2003. Traffic sign recognition and analysis for intelligent vehicles. Image and Vision Computing, 21: 247-258.
6. Soetedjo, A. and Yamada, K. Fast and robust traffic sign detection. IEEE International Conference on Systems, Man and Cybernetics. pp.1341-1346.
7. Gao, X. W., Podladchikova, L. and Shaposhnikov, D. 2005. Recognition of traffic signs based on their colour and shape features extracted using human vision models. Journal of Visual Communication and Image Representation,: 675-685.
8. Lu, K., Wang, C. and Chen, S. 2008. Traffic light recognition [J]. Journal of the Chinese Institute of Engineers, 31(6): 1069-1075.
9. Gong, J., Jiang, Y. and Xiong, G. 2010. "The recognition and tracking of traffic lights based on color segmentation and CAMSHIFT for intelligent vehicles". In IEEE Intelligent Vehicles Symposium, 431-435. San Diego, CA, USA: University of California.
10. Omachi, M. and Omachi, S. 2009. Traffic light detection with color and edge information. Computer Science and Information Technology,: 284-287.
11. Omachi, M. and Omachi, S. Detection of traffic light using structural information. The IEEE International Conference on Signal Processing (ICSP). pp.809-812.
12. Lindner, F., Kressel, U. and Kaelberer, S. 2004. "Robust recognition of traffic signals". In IEEE Intelligent Vehicles Symposium [C] 49-53. Piscataway, NJ, USA
13. Chung, Y., Wang, I. and Chen, S. 2002. A vision-based traffic light detection system at intersections. Journal of National Taiwan Normal University: Mathematics, Science & Technology, 47: 67-86.
14. Yung, N. and Lai, A. 2001. An effective video analysis method for detecting red light runners. IEEE Trans. Vehicular Technology, 50: 1074-1084.
15. Kim, Y. K., Kim, K. W. and Yang, X. Real time traffic light recognition system for color vision deficiencies. IEEE International Conference on Mechatronics and Automation. pp.76-81. Washington, DC
16. Shen, Y., Ozguner, U. and Redmill, K. 2009. "A robust video based traffic light detection algorithm for intelligent vehicles". In IEEE Intelligent Vehicles Symposium [C] 521-526. Piscataway, NJ, USA
17. Charette, R. d. and Nashashibi, F. Traffic light recognition using image processing compared to learning processes. The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems. pp.333-338. St. Louis, USA
18. Charette, R. d. and Nashashibi, F. 2009. "Real time visual traffic lights recognition based on spot light detection and adaptive traffic lights templates". In IEEE Intelligent Vehicles Symposium [C] 358-363. Piscataway, NJ, USA
19. Gonzalez, R. and Woods, R. 1992. Digital Image Processing, Addison-Wesley.
20. Chang, Y. and Li, X. 1994. Adaptive image region-growing. IEEE Transactions on Image Processing,: 868-872.
21. Lewis, J. P. Fast normalized cross-correlation, Industrial Light and Magic.