dc.contributor.author | Peiris, Akila | |
dc.contributor.author | Edirisuriya, EATA | |
dc.contributor.author | Athuraliya, CD | |
dc.contributor.author | Jayasooriya, Isuru | |
dc.date.accessioned | 2020-12-31T20:37:54Z | |
dc.date.available | 2020-12-31T20:37:54Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | http://ir.kdu.ac.lk/handle/345/2953 | |
dc.description.abstract | Abstract -The ever growing number of
vehicles in a country present a variety of
problems including but not limited to;
infrastructural problems, air and water
pollution and accidents with the latter being
the most apparent. The main cause for this
being traffic violations. This research was
carried out with the intention of detecting
motor traffic violations using CCTV footages.
While there have been attempts to create
automated traffic violation detection
systems over the years, these studies have
mostly been focused on more streamlined
and sparse traffic conditions such as
highways. But, the type of traffic conditions
observed in Sri Lanka among other
developing countries are unruly and chaotic.
This paper proposes an automated real-time
traffic violation detection system for highly
congested and unruly road traffic conditions.
The proposed system uses computer vision
techniques, machine learning technology in
creating a traffic violation detection system. | en_US |
dc.language.iso | en | en_US |
dc.subject | Computer Vision | en_US |
dc.subject | Traffic Violation Detection | en_US |
dc.subject | Kalman Filter | en_US |
dc.subject | Haar Detection | en_US |
dc.title | Computer Vision Based Approach for Traffic Violation Detection | en_US |
dc.type | Article Full Text | en_US |
dc.identifier.journal | 13th International Research Conference General Sir John Kotelawala Defence University | en_US |
dc.identifier.pgnos | 136-139 | en_US |