Traffic Signs Color Detection and Segmentation in Poor Light Conditions

This paper presents a new algorithm for color detection and segmentation of road signs in poor light conditions. The images were taken by a digital camera mounted in a car. The RGB channels of the digital images were enhanced separately by histogram equalization, and then a color constancy algorithm was applied to extract the true colors of the sign. The resultant image was then converted into HSV color space, and segmented to extract the colors of the road signs. The method was tested on outdoor images in different poor light conditions such as fog and snow, and they show high robustness. This project is part of the research taking place at Dalarna University Sweden in the field of the Intelligent Transport Systems (ITS).