Real-Time Traffic Sign Detection And Recognition Using Raspberry Pi

Md Isa, Ida Syafiza and Choy, Ja Yeong and Mohd Shaari Azyze, Nur Latif Azyze (2022) Real-Time Traffic Sign Detection And Recognition Using Raspberry Pi. International Journal Of Electrical And Computer Engineering (IJECE), 12 (1). pp. 331-338. ISSN 2088-8708

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Abstract

Nowadays, the number of road accident in Malaysia is increasing expeditiously. One of the ways to reduce the number of road accident is through the development of the advanced driving assistance system (ADAS) by professional engineers. Several ADAS system has been proposed by taking into consideration the delay tolerance and the accuracy of the system itself. In this work, a traffic sign recognition system has been developed to increase the safety of the road users by installing the system inside the car for driver’s awareness. TensorFlow algorithm has been considered in this work for object recognition through machine learning due to its high accuracy. The algorithm is embedded in the Raspberry Pi 3 for processing and analysis to detect the traffic sign from the real-time video recording from Raspberry Pi camera NoIR. This work aims to study the accuracy, delay and reliability of the developed system using a RaspberryPi 3 processor considering several scenarios related to the state of the environment and the condition of the traffic signs. A real-time testbed implementation has been conducted considering twenty different traffic signs and the results show that the system has more than 90% accuracy and is reliable with an acceptable delay

Item Type:	Article
Uncontrolled Keywords:	Accuracy, delay, recognition, reliability, traffic sign
Divisions:	Faculty of Electronics and Computer Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	06 May 2022 10:13
Last Modified:	24 May 2023 14:06
URI:	http://eprints.utem.edu.my/id/eprint/25913
Statistic Details:	View Download Statistic

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