Abstract 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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    Title :

    Vehicle Speed Determination and License Plate Localization from Monocular Video Streams


    Contributors:


    Publication date :

    2019-11-01


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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