In last couple of decades, the technological advancements in image and video processing has brought great revolution in our life. Some of the key areas where these advancements have played a key role are: autonomous vehicles, drone technology, crowd monitoring, traffic monitoring, object tracking etc. Nowadays a lot of work is under process for improving capabilities of autonomous vehicles and driver assisted systems. Our focus in this paper is related to automated traffic light detection system with improved capabilities in terms of time complexity and accuracy. The time complexity is directly related to image or video quality with regard to resolution of video and the accuracy is often compromised because of identification of similar objects. The similar objects often appear in video frames when each frame of video is analyzed completely. In order to solve the problem of real time detection of traffic lights in a high-resolution video having 30 frames per second with a resolution of 1280 × 720, we propose an algorithm that systematically searches in middle 70% region of each frame. The proposed algorithm optimizes the search space by dividing middle region into 3. There are three methods for searching and registering a traffic light is proposed in this paper. The basic concept is at single instance a traffic light can exist on one of these three regions. These trategies help in reducing computation complexity tremendously. The Hough Circle Transform technique of image processing is exploited to accurately detect red and green circles of light in the traffic light. Efficacy of the proposed technique in terms of improved time and accuracy is demonstrated on a real dataset collected from Nexar (dashcam mobile solution provider), it encompasses different illumination conditions: day, evening, night, cludy weather and rain etc
