Adaptive Background Extraction for Video Based Traffic Counter Application Using Gaussian Mixture Models Algorithm
Abstract: The big cities in
the world always face the traffic jam. This problem is caused by the increasing
number of vehicle from time to time and the increase of vehicle is not
anticipated with the development of new road section that is adequate. One
important aspect in the traffic management concept is the need of traffic
density data of every road section. Therefore, the purpose of this paper is to
analyze the possibility of optimization on the use of video file recorded from
CCTV camera for the visual observation and the tool for counting traffic
density. The used method in this paper is adaptive background extraction with
Gaussian Mixture Models algorithm. It is expected to be the alternative
solution to get the data of traffic density with a quite adequate accuracy as
one of aspects for decision making process in the traffic engineering
Keywords: traffic management
system; traffic density counter; adaptive background extraction; gaussian
mixture models
Author: Raymond Sutjiadi,
Endang Setyati, Resmana Lim
Journal Code: jptkomputergg150115
