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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU119856" target="_blank" >RIV/00216305:26220/16:PU119856 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1051/matecconf/20166817002" target="_blank" >http://dx.doi.org/10.1051/matecconf/20166817002</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1051/matecconf/20166817002" target="_blank" >10.1051/matecconf/20166817002</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MATEC Web of Conferences

ISSN

2261-236X

e-ISSN

—

Svazek periodika

68

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

FR - Francouzská republika

Počet stran výsledku

6

Strana od-do

1-6

Kód UT WoS článku

000387731800087

EID výsledku v databázi Scopus

2-s2.0-84982162311