| Issue |
MATEC Web Conf.
Volume 68, 2016
2016 The 3rd International Conference on Industrial Engineering and Applications (ICIEA 2016)
|
|
|---|---|---|
| Article Number | 17002 | |
| Number of page(s) | 6 | |
| Section | Image Processing | |
| DOI | https://doi.org/10.1051/matecconf/20166817002 | |
| Published online | 01 August 2016 | |
Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification
Brno University of Technology, Department of Control and Instrumentation, 61600 Brno, Czech Republic
a Corresponding author: horak@feec.vutbr.cz
The paper describes a colour-based segmentation method of European traffic signs for detection in an image and a feature-based recognition method for categorizing them into given classes. At first, we have performed analysis of several well-known colour spaces as the RGB, HSV and YCbCr often used for segmentation purposes. The HSV colour space has been chosen as the most convenient for segmentation step and colour-based models of traffic signs representatives were created. Next, the fast radial symmetry (FRS) detection method and the Harris corner detector were used to recognize circles, triangles and squares as main geometrical shapes of the traffic signs. For these purposes a new gallery of real-life images containing traffic signs has been created and analysed. Overall efficiency of our recognition method is approx. 93 % on our gallery and is usable for real-time implementations.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.