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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Main Authors: Maćkowski Michał, Sawiski Michał, Walczyszyn Wojciech
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201925203014
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spelling 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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