Sutjiadi, Raymond and Setyati, Endang and Lim, Resmana (2015) Adaptive Background Extraction for Video Based Traffic Counter Application Using Gaussian Mixture Models Algorithm. Telkomnika, 13 (3). pp. 1006-1013. ISSN 1693-6930
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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 adequate new road section. 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 visual observation and 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 traffic density data with a quite adequate accuracy as one of aspects for decision making process in the traffic engineering.
| Item Type: | Article |
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| Uncontrolled Keywords: | traffic management system, traffic density counter, adaptive background extraction, gaussian mixture models |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Information Technology > Informatics Department |
| Depositing User: | P3M IKADO |
| Date Deposited: | 11 Jan 2018 09:39 |
| Last Modified: | 11 Jan 2018 09:39 |
| URI: | http://repository.ikado.ac.id/id/eprint/9 |
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