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Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges
The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539654/ https://www.ncbi.nlm.nih.gov/pubmed/31064098 http://dx.doi.org/10.3390/s19092093 |
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author | Wali, Safat B. Abdullah, Majid A. Hannan, Mahammad A. Hussain, Aini Samad, Salina A. Ker, Pin J. Mansor, Muhamad Bin |
author_facet | Wali, Safat B. Abdullah, Majid A. Hannan, Mahammad A. Hussain, Aini Samad, Salina A. Ker, Pin J. Mansor, Muhamad Bin |
author_sort | Wali, Safat B. |
collection | PubMed |
description | The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system. |
format | Online Article Text |
id | pubmed-6539654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-65396542019-06-04 Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges Wali, Safat B. Abdullah, Majid A. Hannan, Mahammad A. Hussain, Aini Samad, Salina A. Ker, Pin J. Mansor, Muhamad Bin Sensors (Basel) Review The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system. MDPI 2019-05-06 /pmc/articles/PMC6539654/ /pubmed/31064098 http://dx.doi.org/10.3390/s19092093 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Wali, Safat B. Abdullah, Majid A. Hannan, Mahammad A. Hussain, Aini Samad, Salina A. Ker, Pin J. Mansor, Muhamad Bin Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges |
title | Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges |
title_full | Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges |
title_fullStr | Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges |
title_full_unstemmed | Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges |
title_short | Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges |
title_sort | vision-based traffic sign detection and recognition systems: current trends and challenges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539654/ https://www.ncbi.nlm.nih.gov/pubmed/31064098 http://dx.doi.org/10.3390/s19092093 |
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