Abstract

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.

Details

Title
Mobile system for road sign detection and recognition with template matching
Author
Maćkowski, Michał; Sawiski, Michał; Walczyszyn, Wojciech
Section
Computational Artificial Intelligence
Publication year
2019
Publication date
2019
Publisher
EDP Sciences
ISSN
22747214
e-ISSN
2261236X
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2276903131
Copyright
© 2019. This work is licensed under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.