Accurate vehicle detection using stereo vision for toll collection systems

We propose accurate vehicle detection using stereo images for toll collection systems. Conventional methods such as inductive loop sensors and laser scanners have disadvantages for equipment and installation costs. We have developed stereo vision-based depth measuring methods to detect a body of vehicles that achieve higher detection rates. Configurations of stereo cameras and algorithms are specialized for toll collection systems. Traffic data over 10,000 vehicles are used to confirm the accuracy of detection. The results indicate the proposed our approach will realize sufficient performance for toll collection systems and realize low cost vehicle detection for intelligent infrastructures for transportation.