Vehicle Speed Determination and License Plate Localization from Monocular Video Streams

Traffic surveillance is an important aspect of road safety these days as the number of vehicles is increasing rapidly. In this paper, a system is generated for automatic vehicle detection and speed estimation. The vehicle detection and tracking are done through optical flow and centroid tracking using frames of the low-resolution video. The vehicle speed is detected using the relation between the pixel motion and the actual distance. The dataset is taken from the system (Luvizon et al. in A video-based system for vehicle speed measurement in urban roadways. IEEE Trans Intell Transp Syst 1–12, 2016 [1]). The measured speeds have an average error of +0.63 km/h, staying inside [−6, +7] km/h in over 90% of the cases. The license plate localization is done on the vehicle detected by extracting the high-frequency information and using the morphological operations. This algorithm can be used to detect the speed of multiple vehicles in the frame. The measured speeds have a standard deviation error of 4.5 km/h, which is higher than that in the system (Luvizon et al. in A video-based system for vehicle speed measurement in urban roadways. IEEE Trans Intell Transp Syst 1–12, 2016 [1]) by 2 km/h. But our algorithm uses a low-resolution video which reduces the processing time of the system.

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