Automated road sign inventory system based on stereo vision and tracking

Detection, recognition, and positioning of road signs are critical components of a roadway asset management system. In this research, a stereo vision-based system is developed to conduct automated road sign inventory. The system in real time integrates and synchronizes the data streams from multiple sensors of high-resolution cameras, Differential Global Positioning System receivers, Distance Measurement Instrument, and Inertial Measurement Unit. Algorithms are developed based on data sets from the multiple positioning sensors to determine the positions of the moving vehicle and the orientation of the cameras. The key findings from the research include feature extraction and analysis that are applied for automated sign detection and recognition in the Right-of-Way (ROW) images, implementing a tracking algorithm of the candidate sign region among the image frames so the same signs are not counted more than once in an image sequence, and implementing stereo vision technique to compute the world coordinates of the road sign from the stereo-paired ROW images. Particular techniques are employed to conduct all data acquisition and analysis in real time onboard the vehicle. This system is an advanced alternative to traditional inventory methods in terms of safety and efficiency.