PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

 

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Real-Time Traffic Sign Recognition Using Deep Learning

Ananya Belagodu Shivayogi, Nehal Chakravarthy Matasagara Dharmendra, Anala Maddur Ramakrishna and Kolala Nagaraju Subramanya

Pertanika Journal of Science & Technology, Volume 31, Issue 1, January 2023

DOI: https://doi.org/10.47836/pjst.31.1.09

Keywords: DeepStream, Indian traffic sign dataset, NVIDIA Jetson Nano, traffic sign detection, YOLOv4

Published on: 3 January 2023

Traffic Sign Recognition (TSR) is one of the most sought-after topics in computer vision, mostly due to the increasing scope and advancements in self-driving cars. In our study, we attempt to implement a TSR system that helps a driver stay alert during driving by providing information about the various traffic signs encountered. We will be looking at a working model that classifies the traffic signs and gives output in the form of an audio message. Our study will be focused on traffic sign detection and recognition on Indian roads. A dataset of Indian road traffic signs was created, based upon which our deep learning model will work. The developed model was deployed on NVIDIA Jetson Nano using YOLOv4 architecture, giving an accuracy in the range of 54.68–76.55% on YOLOv4 architecture. The YOLOv4-Tiny model with DeepStream implementation achieved an FPS of 32.5, which is on par with real-time detection requirements.

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ISSN 0128-7680

e-ISSN 2231-8526

Article ID

JST-3499-2022

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