Vision-based industrial automatic vehicle classifier

Timur Khanipov; Ivan Koptelov; Anton Grigoryev; Elena Kuznetsova; Dmitry Nikolaev

doi:10.1117/12.2181557

14 February 2015 Vision-based industrial automatic vehicle classifier

Timur Khanipov, Ivan Koptelov, Anton Grigoryev, Elena Kuznetsova, Dmitry Nikolaev

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Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 944511 (2015) https://doi.org/10.1117/12.2181557
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy

Abstract

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.

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Timur Khanipov, Timur Khanipov, Ivan Koptelov, Ivan Koptelov, Anton Grigoryev, Anton Grigoryev, Elena Kuznetsova, Elena Kuznetsova, Dmitry Nikolaev, Dmitry Nikolaev, } "Vision-based industrial automatic vehicle classifier", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 944511 (14 February 2015); doi: 10.1117/12.2181557; https://doi.org/10.1117/12.2181557

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