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Research and Practice of Traffic Lights and Traffic Signs Recognition System Based on Multicore of FPGA
Beijing University of Posts and Telecommunications, School of Computer Science
Beijing University of Posts and Telecommunications, School of Computer Science
Beijing University of Posts and Telecommunications, School of Computer Science
Beijing University of Posts and Telecommunications, School of Computer Science
Beijing University of Posts and Telecommunications, School of Computer Science
Beijing University of Posts and Telecommunications, School of Computer Science
- 1 Beijing University of Posts and Telecommunications, School of Computer Science
- 2 Beijing University of Posts and Telecommunications, School of Computer Science
- 3 Beijing University of Posts and Telecommunications, School of Computer Science
- 4 Beijing University of Posts and Telecommunications, School of Computer Science
- 5 Beijing University of Posts and Telecommunications, School of Computer Science
- 6 Beijing University of Posts and Telecommunications, School of Computer Science
Communications and Network·Volume 05 (2013)·Pages 61–64·Published 28 February 2013·DOI10.4236/cn.2013.51B014
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Abstract
This thesis will present the research and practice of traffic lights and traffic signs recognition system based on multicore of FPGA. This system consists of four parts as following: the collection of dynamic images, the preprocessing of gray value, the detection of the edges and the patterning and the judgment of the pattern matching. The multiple cores system is consist of three cores. Each core parallels processes the incoming images from camera collection in terms of different colors and graphic elements. The image data read in from the camera works as the sharing data of the three cores.
KeywordsIntelligent TransportationMulticoreImage ProcessingSOPC
- S. Pan and J. Y. Huang, “SOPC Technique Practical Course,” Tsinghua University Press 2005, pp. 10-13.
- Altera Corp, “NIOS II Processor Reference Handbook,” Altera, 2005, pp. 23-54.
- Altera Corp, “NIOS II Software Developer’S Handbook,” Altera, 2005, pp. 56-78.
- Altera Corp, “Creating Multiprocessor NIOS II System Tutorial,” Altera, 2005, pp. 26-46.
- Altera Corp, “NIOS II Software Developer’S Handbook,” Altera, 2005, pp. 12-40.
- S. Yehu, O. UMIT and R. KEITH, “A robust video based traffic light detection algorithm for intelligent vehicles,” IEEE Intelligent Vehicles Symposium, Washington, DC: IEEE Press, 2009, pp. 521-526.
- D. Yang, K. Q. Li and S. F. Zheng, “Automobile Technique in Intelligent Transportation System,” Automotive Engineering Press 2003, Vol. 25, No. 3, pp. 220-228.
- T.-H. Hwang, I.-H. Joo and S.-I. Cho, “Detection of Traffic Lights for Vision-based Car Navigation System,” PSIVT 2006: Pacific Rim Symposium on Advances in Image and Video Technology, LNCS 4319, Berlin: Springer-Verlag, 2006, pp. 682-691. doi:10.1109/40.285222