Mobile system for road sign detection and recognition with template matching
This paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illumination. The main goal of the system is to assist drivers by...
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EDP Sciences
2019-01-01
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Series: | MATEC Web of Conferences |
Online Access: | https://doi.org/10.1051/matecconf/201925203014 |
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doaj-0306fc39ab8149c587489796fe98d0bf2021-03-02T07:36:20ZengEDP SciencesMATEC Web of Conferences2261-236X2019-01-012520301410.1051/matecconf/201925203014matecconf_cmes2018_03014Mobile system for road sign detection and recognition with template matchingMaćkowski Michał0Sawiski Michał1Walczyszyn WojciechSilesian University of Technology, Institute of InformaticsSilesian University of Technology, Institute of InformaticsThis paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illumination. The main goal of the system is to assist drivers by warning them about the existence of road signs to increase safety during driving. In this paper, the system for detection and recognition of road signs was implemented and tested with the use of Open Source Computer Vision Library (OpenCV). The system consists of two parts. The first part is the detection stage, which is used to detect the signs from the whole image frame and includes the modules: data-image acquisition, image pre-processing and sign detection. During this stage, the impact of Canny edge detector and Hough transform parameters on the quality-level of sign detection was tested. The second part is the recognition stage, whose role is to match the detected object with a priori models of signs in the dataset. In the research, the authors also compared the influence of various image processing algorithms parameters to the time of road sign recognition. The discussion part answers also the question whether the mobile system (smartphone) is robust enough to detect and recognise road sings in real time.https://doi.org/10.1051/matecconf/201925203014 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maćkowski Michał Sawiski Michał Walczyszyn Wojciech |
spellingShingle |
Maćkowski Michał Sawiski Michał Walczyszyn Wojciech Mobile system for road sign detection and recognition with template matching MATEC Web of Conferences |
author_facet |
Maćkowski Michał Sawiski Michał Walczyszyn Wojciech |
author_sort |
Maćkowski Michał |
title |
Mobile system for road sign detection and recognition with template matching |
title_short |
Mobile system for road sign detection and recognition with template matching |
title_full |
Mobile system for road sign detection and recognition with template matching |
title_fullStr |
Mobile system for road sign detection and recognition with template matching |
title_full_unstemmed |
Mobile system for road sign detection and recognition with template matching |
title_sort |
mobile system for road sign detection and recognition with template matching |
publisher |
EDP Sciences |
series |
MATEC Web of Conferences |
issn |
2261-236X |
publishDate |
2019-01-01 |
description |
This paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illumination. The main goal of the system is to assist drivers by warning them about the existence of road signs to increase safety during driving. In this paper, the system for detection and recognition of road signs was implemented and tested with the use of Open Source Computer Vision Library (OpenCV). The system consists of two parts. The first part is the detection stage, which is used to detect the signs from the whole image frame and includes the modules: data-image acquisition, image pre-processing and sign detection. During this stage, the impact of Canny edge detector and Hough transform parameters on the quality-level of sign detection was tested. The second part is the recognition stage, whose role is to match the detected object with a priori models of signs in the dataset. In the research, the authors also compared the influence of various image processing algorithms parameters to the time of road sign recognition. The discussion part answers also the question whether the mobile system (smartphone) is robust enough to detect and recognise road sings in real time. |
url |
https://doi.org/10.1051/matecconf/201925203014 |
work_keys_str_mv |
AT mackowskimichał mobilesystemforroadsigndetectionandrecognitionwithtemplatematching AT sawiskimichał mobilesystemforroadsigndetectionandrecognitionwithtemplatematching AT walczyszynwojciech mobilesystemforroadsigndetectionandrecognitionwithtemplatematching |
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