A Real Time Traffic Light Recognition System

Driving is a challenging task, especially for those with color vision deficiencies. Intelligent Transport Systems (ITS) can provide useful information and make driving safe and convenient. A real time traffic light recognition system is presented in this paper for improving public safety and facilitating color deficient drivers. It may also be included as a part of ITS. The presented system consists of a digital video camera to record traffic lights and a portable PC to process images in real time. It uses various techniques of color detection, feature matching with normalized cross-correlation (NCC), and mathematical shape analysis for the traffic light recognition. For color detection, we obtained an initial solution by using RGB component adjustment, thresholding algorithm, and median filter. In dealing with illumination changes with weather and time, a simple adaptation method was developed. Feature matching with NCC was used after color detection to further detect and recognize the traffic lights. To improve the system's tolerance and robustness, a mathematical shape analysis was undertaken to obtain the final results. Numerous experiments were conducted to demonstrate the effectiveness and practicability of the system with images under different weather conditions. The average recognition ratio is higher than 95% from the testing results. The average processing time is 30 ms per frame, making the system suitable in real time conditions. Audio alert is added to the current system as an integral part of a portable system to be developed.