Hammad Ali, Abu MohammadAlam, Md. ZahangirPaul, Partho Sharothi2014-08-272014-08-2720142014ID 09101014http://hdl.handle.net/10361/3486Cataloged from PDF version of thesis report.Includes bibliographical references (page 27 - 28).This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.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.28 pagesenBRAC 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.Computer science and engineeringBackground segmentationImage processingDensity estimationEmbedded systemTraffic signal systemThesis