Traditional methods and machine learning-based methods for traffic sign detection

Kai Huang

doi:10.1117/12.2655943

12 January 2023 Traditional methods and machine learning-based methods for traffic sign detection

Kai Huang

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 1250929 (2023) https://doi.org/10.1117/12.2655943
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

This article provides a brief overview of a few recent traffic sign detection studies, as well as a review of the concept and structure of traffic sign detection throughout the last decade. The methodology differs in several ways, but it is commonly divided into four distinct aspects. They are methods that are based on color or shape, hybrid-based methods, and methods that are based on machine learning, in that order. Machine learning-based technologies have steadily seized the lead recently because of their superior performance. As a result, the main attention of this study is on machine learning methods, as well as a review of past work, datasets, and performance. The outcomes of experiments using the same methodologies but different approaches are compared.

Citation Download Citation

Kai Huang "Traditional methods and machine learning-based methods for traffic sign detection", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 1250929 (12 January 2023); https://doi.org/10.1117/12.2655943

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