Recognition of traffic signs based on their colour and shape features extracted using human vision models
Gao, Xiaohong W. and Podladchikova, L. N. and Shaposhnikov, D. G. and Hong, K. and Shevtsova, Natalia (2006) Recognition of traffic signs based on their colour and shape features extracted using human vision models. Journal of Visual Communication and Image Representation, 17 (4). pp. 675-685. ISSN 1047-3203
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Colour and shape are basic characteristics of traffic signs which are used both by the driver and to develop artificial traffic sign recognition systems. However, these sign features have not been represented robustly in the earlier developed recognition systems, especially in disturbed viewing conditions. In this study, this information is represented by using a human vision colour appearance model and by further developing existing behaviour model of visions. Colour appearance model CIECAM97 has been applied to extract colour information and to segment and classify traffic signs. Whilst shape features are extracted by the development of FOSTS model, the extension of behaviour model of visions. Recognition rate is very high for signs under artificial transformations that imitate possible real world sign distortion (up to 50% for noise level, 50 m for distances to signs, and 5° for perspective disturbances) for still images. For British traffic signs (n = 98) obtained under various viewing conditions, the recognition rate is up to 95%.
|Research Areas:||A. Middlesex University Schools and Centres > School of Science and Technology > Computer Science > Artificial Intelligence group|
A. Middlesex University Schools and Centres > School of Science and Technology > Computer Science
|Citations on ISI Web of Science:||22|
|Deposited On:||15 Oct 2008 12:32|
|Last Modified:||30 Jan 2015 16:20|
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