Real-time embedded system for traffic sign recognition based on ZedBoard

被引：0
作者：
Wajdi Farhat
Hassene Faiedh
Chokri Souani
Kamel Besbes
机构：
[1] Monastir University,Laboratory of Microelectronics and Instrumentation
[2] Sousse University,National School of Engineers
[3] Sousse University,Higher Institute of Applied Sciences and Technology
[4] Sousse University,Center for Research on Microelectronics and Nanotechnology of Sousse
来源：
Journal of Real-Time Image Processing | 2019年 / 16卷
关键词：
ADAS; Detection; FPGA; Image processing; Real-time; Recognition; Video;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents a design methodology of a real-time embedded system that processes the detection and recognition of road signs while the vehicle is moving. An efficient algorithm was proposed, which operates in two processing steps: the detection and the recognition. Regions of interest were extracted by using the Maximally Stable Extremal Regions Method. For the recognition phase, Oriented FAST and Rotated BRIEF features were used. A hardware system based on the Xilinx Zynq platform was developed. The designed system can achieve real-time video processing while assuring constraints and a high-level accuracy in terms of detection and recognition rates.
引用
收藏
页码：1813 / 1823
页数：10
相关论文
共 77 条
[1]  
Souani C(2014)Efficient algorithm for automatic road sign recognition and its hardware implementation J. Real-Time Image Process. 9 79-93
[2]  
Faiedh H(2010)Goal evaluation of segmentation algorithms for traffic sign recognition IEEE Trans. Intell. Transp. Syst. 11 917-930
[3]  
Besbes K(2016)A hardware/software prototyping system for driving assistance investigations J Real Time Image Process. 11 559-569
[4]  
Gomez-Moreno H(2010)Real-time traffic sign recognition from video by class-specific discriminative features Pattern Recogn. 43 416-430
[5]  
Maldonado-Bascon S(2009)Robust traffic sign shape recognition using geometric matching IET Intell. Transp. Syst. 3 10-18
[6]  
Gil-Jimenez P(2007)Road-Sign Detection and Recognition Based on Support Vector Machines IEEE Trans. Intell. Transp. Syst. 8 264-278
[7]  
Lafuente-Arroyo S(2014)Symmetrical SURF and its applications to vehicle detection and vehicle make and model recognition IEEE Trans. Intell. Transp. Syst. 15 6-20
[8]  
Anders J(2014)Real-time traffic sign recognition in three stages Robot. Auton. Syst. 62 16-24
[9]  
Mefenza M(2012)Real-time detection and recognition of road traffic signs IEEE Trans. Intell. Transp. Syst. 13 1498-1506
[10]  
Bobda C(1998)Autonomous driving goes downtown IEEE Intell. Syst. Their Appl. 13 40-48
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