Colour vision model-based approach for segmentation of traffic signs

Gao, Xiaohong W. and Hong, Kunbin and Passmore, Peter J. and Podladchikova, Lubov and Shaposhnikov, Dmitry (2008) Colour vision model-based approach for segmentation of traffic signs. EURASIP Journal on Image and Video Processing, 2008 . ISSN 1687-5176

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Official URL: http://dx.doi.org/10.1155/2008/386705

Abstract

This paper presents a new approach to segment traffic signs from the rest of a scene via CIECAM, a colour appearance model. This approach not only takes CIECAM into practical application for the first time since it was standardised in 1998, but also introduces a new way of segmenting traffic signs in order to improve the accuracy of colour-based approach. Comparison with the other CIE spaces, including CIELUV and CIELAB, and RGB colour space is also carried out. The results show that CIECAM performs better than the other three spaces with 94%, 90%, and 85% accurate rates for sunny, cloudy, and rainy days, respectively. The results also confirm that CIECAM does predict the colour appearance similar to average observers.

Item Type:Article
Research Areas:Middlesex University Schools and Centres > School of Science and Technology > Computer Science
Middlesex University Schools and Centres > School of Science and Technology > Computer Science > Artificial Intelligence group
Citations on ISI Web of Science:3
ID Code:8435
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Deposited On:21 Feb 2012 09:18
Last Modified:24 Oct 2014 15:18

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