Shadow and highlight invariant colour segmentation algorithm for traffic signs

Document identifier: oai:dalea.du.se:2102
Access full text here:10.1109/ICCIS.2006.252225
Keyword: Natural Sciences, Computer and Information Sciences, Naturvetenskap, Data- och informationsvetenskap, Colour segmentation; colour detection; road signs; outdoor image
Publication year: 2006
Relevant Sustainable Development Goals (SDGs):
SDG 9 Industry, innovation and infrastructure
The SDG label(s) above have been assigned by OSDG.ai

Abstract:

Shadows and highlights represent a challenge to the computer vision researchers due to a variance in the brightness on the surfaces of the objects under consideration. This paper presents a new colour detection and segmentation algorithm for road signs in which the effect of shadows and highlights are neglected to get better colour segmentation results. Images are taken by a digital camera mounted in a car. The RGB images are converted into HSV colour space and the shadow-highlight invariant method is applied to extract the colours of the road signs under shadow and highlight conditions. The method is tested on hundreds of outdoor images under such light conditions, and it shows high robustness; more than 95% of correct segmentation is achieved.

Authors

Hasan Fleyeh

Högskolan Dalarna; Datateknik
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