Traffic density estimation and flow control for video surveillance system
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.
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BRAC University
2014
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| 在线阅读: | http://hdl.handle.net/10361/3486 |
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10361-34862022-01-26T10:05:00Z Traffic density estimation and flow control for video surveillance system Paul, Partho Sharothi Hammad Ali, Abu Mohammad Alam, Md. Zahangir Department of Computer Science and Engineering, BRAC University Computer science and engineering Background segmentation Image processing Density estimation Embedded system Traffic signal system This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. Cataloged from PDF version of thesis report. Includes bibliographical references (page 27 - 28). Video monitoring and surveillance have been widely used in traffic surveillance system. It is important to know the road traffic density in predefined traffic videos especially in mega cities like Dhaka for signal control and effective traffic management .In this paper, I researched on vehicle density estimation and flow control for outdoor traffic surveillance is presented. A common approach is to perform background subtraction, which identifies moving objects from the portion of a video frame that differ significantly from a background model. For Background modeling I used Frame differencing method as for density estimation as our background is static. My experiments shows static background subtraction algorithms with adaptive thresholding, post-processing with morphological image processing can produce good results with much lower computational complexity. Depending on the number of vehicle my embedded system will generate signal effectively to Control the flow of traffic in the road. Partho Sharothi Paul B. Computer Science and Engineering 2014-08-27T09:24:47Z 2014-08-27T09:24:47Z 2014 2014 Thesis ID 09101014 http://hdl.handle.net/10361/3486 en BRAC University thesis 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. 28 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Computer science and engineering Background segmentation Image processing Density estimation Embedded system Traffic signal system |
| spellingShingle |
Computer science and engineering Background segmentation Image processing Density estimation Embedded system Traffic signal system Paul, Partho Sharothi Traffic density estimation and flow control for video surveillance system |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. |
| author2 |
Hammad Ali, Abu Mohammad |
| author_facet |
Hammad Ali, Abu Mohammad Paul, Partho Sharothi |
| format |
Thesis |
| author |
Paul, Partho Sharothi |
| author_sort |
Paul, Partho Sharothi |
| title |
Traffic density estimation and flow control for video surveillance system |
| title_short |
Traffic density estimation and flow control for video surveillance system |
| title_full |
Traffic density estimation and flow control for video surveillance system |
| title_fullStr |
Traffic density estimation and flow control for video surveillance system |
| title_full_unstemmed |
Traffic density estimation and flow control for video surveillance system |
| title_sort |
traffic density estimation and flow control for video surveillance system |
| publisher |
BRAC University |
| publishDate |
2014 |
| url |
http://hdl.handle.net/10361/3486 |
| work_keys_str_mv |
AT paulparthosharothi trafficdensityestimationandflowcontrolforvideosurveillancesystem |
| _version_ |
1814307165039493120 |