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

Farhat Wajdi; Faiedh Hassene; Souani Chokri; Besbes Kamel

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

机译：基于ZedBoard的交通标志实时嵌入式系统

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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.

机译：本文提出了一种实时嵌入式系统的设计方法，该系统可在车辆行驶时处理路标的检测和识别。提出了一种高效的算法，该算法分两个处理步骤：检测和识别。使用最大稳定极值区域方法提取感兴趣的区域。对于识别阶段，使用了定向的FAST和Rotated Brief功能。开发了基于Xilinx Zynq平台的硬件系统。设计的系统可以实现实时视频处理，同时确保检测和识别率方面的约束和高级别的准确性。

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来源
《Journal of Real-Time Image Processing》 |2019年第5期|1813-1823|共11页
作者
Farhat Wajdi; Faiedh Hassene; Souani Chokri; Besbes Kamel;
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作者单位

Monastir Univ Lab Microelect & Instrumentat Monastir Tunisia|Sousse Univ Natl Sch Engineers Sousse Tunisia;

Monastir Univ Lab Microelect & Instrumentat Monastir Tunisia|Sousse Univ Higher Inst Appl Sci & Technol Sousse Tunisia;

Monastir Univ Lab Microelect & Instrumentat Monastir Tunisia|Sousse Univ Ctr Res Microelect & Nanotechnol Sousse Sousse Tunisia;

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正文语种 eng
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关键词
ADAS; Detection; FPGA; Image processing; Real-time; Recognition; Video;

机译：ADAS;检测;FPGA;图像处理;即时的;承认;视频;

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专利

1. Embedded Real-Time System for Traffic Sign Recognition on ARM Processor [J] . International Journal of Applied Metaheuristic Computing . 2020,第2期

机译：嵌入式实时系统，用于ARM处理器上的交通标志识别
2. An efficient traffic sign recognition based on graph embedding features [J] . Gudigar Anjan, Chokkadi Shreesha, Raghavendra U., Neural computing & applications . 2019,第2期

机译：基于图形嵌入功能的高效流量标志识别
3. Sparse-Representation-Based Graph Embedding for Traffic Sign Recognition [J] . Lu K., Ding Z., Ge S. Intelligent Transportation Systems, IEEE Transactions on . 2012,第4期

机译：基于稀疏表示的图形嵌入用于交通标志识别
4. A Model for Real-Time Traffic Signs Recognition Based on the YOLO Algorithm - A Case Study Using Vietnamese Traffic Signs [C] . An Cong Tran, Duong Lu Dien, Hiep Xuan Huynh, International conference on future data and security engineering . 2019

机译：基于YOLO算法的交通标志实时识别模型-以越南交通标志为例。
5. Embedded system design for traffic sign recognition using machine learning algorithms. [D] . Han, Yan. 2016

机译：使用机器学习算法进行交通标志识别的嵌入式系统设计。
6. Real-Time Traffic Sign Detection and Recognition Method Based on Simplified Gabor Wavelets and CNNs [O] . Faming Shao, Xinqing Wang, Fanjie Meng, 2018

机译：基于简化Gabor小波和CNN的实时交通标志检测与识别方法
7. Real-Time Traffic Sign Recognition System based on Colour Image Segmentation [O] . Vishal R. Deshmukh, G. K. Patnaik, Ph. D, 2014

机译：基于彩色图像分割的实时交通标志识别系统

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

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