Oni, Aderonke A and Kajoh, Nicholas (2019) Video-Based Vehicle Counting System for Urban Roads in Nigeria Using Yolo and DCF-CSR Algorithms. International Journal of Engineering Research and Technology, 12 (12). pp. 2550-2558. ISSN 0974-3154
![[img]](http://eprints.covenantuniversity.edu.ng/style/images/fileicons/application_pdf.png) |
PDF
Download (537kB) |
Abstract
This study improves the traffic situation on, and condition of Nigerian roads by implementing a vehicle counting system that provides accurate data for traffic control agencies and systems. After comparing different detection and tracking algorithms, You Only Look Once and Discriminative Correlation Filter with Channel and Spatial Reliability were chosen as detection and tracking algorithms respectively for the system. The system was implemented using Python programming language and OpenCV. The significances of this system include estimating traffic flow on a given road per time, predicting future traffic conditions, understanding traffic patterns and the factors that affect them, and optimizing existing manual traffic management systems.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Vehicle counting, detection, tracking, YOLO, DCF-CSR |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Mrs Patricia Nwokealisi |
| Date Deposited: | 25 Jun 2021 21:11 |
| Last Modified: | 25 Jun 2021 21:11 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/14985 |
Actions (login required)
 |
View Item |
