@inproceedings{0e4327845f424569a00ba43dd3e56820,
title = "Speed Monitoring for Multiple Vehicle Using Closed Circuit Television (CCTV) Camera",
abstract = "The large number of CCTV installations (Closed-Circuit Television) on the road can assist in monitoring and managing traffic conditions. There are several systems that use CCTV for monitoring traffic, one of which is the monitoring of vehicle speed. However, the current speed monitoring system utilizing the Camera has not been able to capture images of vehicles automatically on the road. Because the speed violation system cannot distinguish between infringing vehicles or not if there are many vehicles detected. Focusing on this issue, we propose a system that can monitor the speed of some vehicles and determine which vehicles have been detected breaking speed by tracking the vehicle using a matching-based method. We use the projective transformation method to calculate speed of a vehicle. This method is used to transform the capture image to the top view image in a rectangle shape. Based on the results of testing on the system in frame rate 30 fps, the accuracies of calculation speed are 97.01% when no shadow and 83.86% when a shadow. This system can also determine the type of car or motorcycle vehicle detected breaking with an accuracy of 89.62%.",
keywords = "CCTV Camera, Matching-based, Projective Transformation, Vehicle speed",
author = "A. Kurniawan and A. Ramadlan and Yuniarno, {E. M.}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 ; Conference date: 26-11-2018 Through 27-11-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/CENIM.2018.8710854",
language = "English",
series = "2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 - Proceeding",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "88--93",
booktitle = "2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 - Proceeding",
address = "United States",
}