Detail publikace

Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification

HORÁK, K. ČÍP, P. DAVÍDEK, D.

Originální název

Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Traffic sign, colour segmentation, shape recognition.

Autoři

HORÁK, K.; ČÍP, P.; DAVÍDEK, D.

Vydáno

1. 8. 2016

Nakladatel

EDP Sciences

Místo

EDP Sciences - France

ISBN

2261236X

Kniha

Proceedings of the 3rd International Conference on Industrial Engineering and Applications 2016.

Edice

Volume 68

Číslo edice

17002

ISSN

2261-236X

Periodikum

MATEC Web of Conferences

Ročník

68

Číslo

1

Stát

Francouzská republika

Strany od

1

Strany do

6

Strany počet

6

URL

http://dx.doi.org/10.1051/matecconf/20166817002

Plný text v Digitální knihovně

http://hdl.handle.net/11012/203162

BibTex

@article{BUT127252,
  author="Karel {Horák} and Pavel {Číp} and Daniel {Davídek}",
  title="Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification",
  journal="MATEC Web of Conferences",
  year="2016",
  volume="68",
  number="1",
  pages="1--6",
  doi="10.1051/matecconf/20166817002",
  issn="2261-236X",
  url="http://dx.doi.org/10.1051/matecconf/20166817002"
}