Embedded Real-Time System for Traffic Sign Recognition on ARM Processor

Author:

Faiedh Hassene1,Farhat Wajdi1ORCID,Hamdi Sabrine2,Souani Chokri3ORCID

Affiliation:

1. Higher Institute of Applied Sciences and Technology. Sousse University, Sousse, Tunisia

2. National School of Engineers, Sousse University, Sousse, Tunisia

3. Higher Institute of Applied Sciences and Technology, Sousse University, Sousse, Tunisia

Abstract

This article proposes the design of a novel hardware embedded system used for automatic real-time road sign recognition. The algorithm used was implemented in two main steps. The first step, which detects the road signs, is performed by the maximally stable extremal region method on HSV color space. The second step enables the recognition of the detected signs by using the oriented fast and rotated brief features method. The novelty of the embedded hardware system, on an ARM processor, leads to a real-time implementation of the ADAS applications. The proposed system was tested on the Belgium Traffic Sign Detection and Recognition Benchmark and on the German Traffic Signs Datasets. The proposed approach attained a high detection and recognition rate with real-world situations. The achieved results are acceptable when compared to state-of-the-art systems.

Publisher

IGI Global

Subject

Decision Sciences (miscellaneous),Computational Mathematics,Computational Theory and Mathematics,Control and Optimization,Computer Science Applications,Modeling and Simulation,Statistics and Probability

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A comprehensive review on applications of Raspberry Pi;Computer Science Review;2024-05

2. A Real-Time Traffic Sign Recognition Method Using a New Attention-Based Deep Convolutional Neural Network for Smart Vehicles;Applied Sciences;2023-04-11

3. A Robust Network for Embedded Traffic Sign Recognition;2021 11th International Conference on Computer Engineering and Knowledge (ICCKE);2021-10-28

4. Boiler Temperature and Pressure Monitoring System for Thermal Power Plant through LabVIEW;IOP Conference Series: Materials Science and Engineering;2020-12-01

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