Vehicle passes detector based on multi-sensor analysis

D. Bocharov; D. Sidorchuk; I. Konovalenko; I. Koptelov

doi:10.1117/12.2181378

14 February 2015 Vehicle passes detector based on multi-sensor analysis

D. Bocharov, D. Sidorchuk, I. Konovalenko, I. Koptelov

Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 944510 (2015) https://doi.org/10.1117/12.2181378
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy

Abstract

The study concerned deals with a new approach to the problem of detecting vehicle passes in vision-based automatic vehicle classification system. Essential non-affinity image variations and signals from induction loop are the events that can be considered as detectors of an object presence. We propose several vehicle detection techniques based on image processing and induction loop signal analysis. Also we suggest a combined method based on multi-sensor analysis to improve vehicle detection performance. Experimental results in complex outdoor environments show that the proposed multi-sensor algorithm is effective for vehicles detection.

Citation Download Citation

D. Bocharov, D. Sidorchuk, I. Konovalenko, and I. Koptelov "Vehicle passes detector based on multi-sensor analysis", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 944510 (14 February 2015); https://doi.org/10.1117/12.2181378

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