In this paper, a traffic light recognition system for real-time processing has been proposed. The conventional saliency map is hardly applicable to traffic light recognition systems due to its high complexity. The proposed system is made for a real-time traffic light recognition system by optimizing the saliency map. The proposed system maintains the recognition rate and reduces the complexity of the system when compared to the conventional system.
Accurate detection of traffic lights is very important for the advanced driver assistance system (ADAS). There have been many research developments in this area. However, conventional of image processing methods are usually sensitive to varying illumination conditions. This paper proposes a traffic light detection algorithm to overcome this situation. The proposed algorithm first detects the candidates of traffic light using the proposed color map and hue-saturation-value (HSV) Traffic lights are then detected using the conventional histogram of oriented gradients (HOG) descriptor and support vector machine (SVM). Finally, the proposed Multilayer HOG descriptor is used to determine the direction information indicated by traffic lights. The proposed algorithm shows a high detection rate in real-time.
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