Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification
Loading...
Date
2016-08-01
Authors
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
EDP Sciences
Altmetrics
Abstract
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.
Description
Citation
MATEC Web of Conferences. 2016, vol. 68, issue 1, p. 1-6.
http://dx.doi.org/10.1051/matecconf/20166817002
http://dx.doi.org/10.1051/matecconf/20166817002
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en