Recognition Of Traffic Lights In Urban Traffic Scenes Using Color Space Model

In order to identify the status of traffic lights in urban traffic scenes effectively, a recognition method of traffic lights using HSV color space model is proposed in this paper. Firstly, the median filter and the light compensation algorithm are used to preprocess images of urban traffic scenes. Secondly, the template matching method of traffic lights and the Bhattacharyya coefficient are used to detection of the traffic lights area in images of traffic scenes. Finally, the status of traffic lights in urban traffic scenes are identified using HSV color space model. The experimental results show that the proposed recognition method of traffic lights using HSV color space model offers the best performance than RGB color space model and YCbCr color space model. The recognition accuracies of red, green and yellow traffic lights are 96.67%, 95.0% and 88.67%, respectively.