Vision-based industrial automatic vehicle classifier
Timur Khanipov, Ivan Koptelov, Anton S. Grigoryev, Elena G. Kuznetsova, Dmitry Nikolaev · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
The paper describes the automatic motor vehicle video stream based classification system. The system determines vehicle type at payment collection plazas on toll roads. Classification is performed in accordance with a preconfigured set of rules which determine type by number of wheel axles, vehicle length, height over the first axle and full height. These characteristics are calculated using various computer vision algorithms: contour detectors, correlational analysis, fast Hough transform, Viola-Jones detectors, connected components analysis, elliptic shapes detectors and others. Input data contains video streams and induction loop signals. Output signals are vehicle enter and exit events, vehicle type, motion direction, speed and the above mentioned features.