dc.contributor.advisor | Uddin, Jia | |
dc.contributor.author | Chowdhury, Md. Fahim | |
dc.contributor.author | Biplob, Md Ryad Ahmed | |
dc.date.accessioned | 2018-05-17T05:37:01Z | |
dc.date.available | 2018-05-17T05:37:01Z | |
dc.date.copyright | 2018 | |
dc.date.issued | 2018-04 | |
dc.identifier.other | ID 14101221 | |
dc.identifier.other | ID 14101182 | |
dc.identifier.uri | http://hdl.handle.net/10361/10164 | |
dc.description | This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 17-18). | |
dc.description.abstract | In recent times, traffic jam has become a common problem in the major cities all over the world.
Our capital city Dhaka is no exception. Numbers of people are being victim of traffic jam each
day. The main causes of such situation are more cars on the street, poor traffic management and
lack of proper infrastructure. In this paper, we propose a dynamic traffic control system by
measuring the traffic density at the intersections by real time video feeds and image processing.
We used MOG algorithm for background subtraction method and for foreground detection to
keep the count of the cars in each lane. The traffic lights at the intersections will change
dynamically according to the conditions of traffic that will be detected from the video feeds. | en_US |
dc.description.statementofresponsibility | Md. Fahim Chowdhury | |
dc.description.statementofresponsibility | Md Ryad Ahmed Biplob | |
dc.format.extent | 18 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | Traffic density | en_US |
dc.subject | Traffic control | en_US |
dc.subject | Computer | en_US |
dc.subject | Real time traffic | en_US |
dc.title | Real time traffic density measurement using computer vision and dynamic traffic control | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |