Digital Image Processing
Visual sign information extraction and identification by deformable models for intelligent vehicles
IEEE Transactions on Intelligent Transportation Systems
Traffic light recognition using image processing compared to learning processes
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
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A recent trend of car navigation system is using actual video captured by camera equipped on a vehicle. The video-based navigation systems displays guidance information overlaid onto video before reaching a crossroad, so it is essential to detect where the crossroads are in the video frame. In this paper, we suggest a detection method for traffic lights that is used for estimating location of crossroads in image. Suggested method can detect traffic lights in a long distance, and estimates pixel location of crossroad that is important information to visually represent guidance information on video. We suggest a new method for traffic light detection that processes color thresholding, finds center of traffic light by Gaussian mask, and verifies the candidate of traffic light using suggested existence-weight map. Experiments show that the detection method for traffic signs works effectively and robustly for outdoor video and can used for video-based navigation system.