Video analysis of vehicular flows for road traffic monitoring

Video Analysis of Vehicular Flows for Road Traffic Monitoring” is a final year project that aims to develop a real time computer vision system that can collect traffic data, detect traffic incidents and has practical applications on intelligent traffic monitoring. Videos are sourced from Land Transp...

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Main Author: Ong, Kai Sin.
Other Authors: Ang Yew Hock
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/14741
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-14741
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spelling sg-ntu-dr.10356-147412019-12-10T11:43:41Z Video analysis of vehicular flows for road traffic monitoring Ong, Kai Sin. Ang Yew Hock School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision DRNTU::Engineering::Civil engineering::Transportation Video Analysis of Vehicular Flows for Road Traffic Monitoring” is a final year project that aims to develop a real time computer vision system that can collect traffic data, detect traffic incidents and has practical applications on intelligent traffic monitoring. Videos are sourced from Land Transport Authority (LTA) and the objectives of this project is to create a program that can detect traffic events through streaming from the IP network camera and alert the end user on the traffic conditions on the particular highway. In this report, theoretical and technical aspects of computer vision techniques are explained in detail. In theoretical aspects of computer vision techniques, techniques that will be explained in depth will be grayscaling, image differencing, edge detection and automatic thresholding. Some techniques have been implemented in the proposed system. Also, technical aspects of the prototype will be discussed. The prototype is able to retrieve images from the live streaming via the network camera and preprocess the images using image differencing. Foreground extraction is retrieved and pixel intensity is calculated by the system which serves as a guide and signal for traffic flow at the point of time. This helps to classify the congestion level. Bachelor of Engineering 2009-01-30T07:46:10Z 2009-01-30T07:46:10Z 2008 2008 Final Year Project (FYP) http://hdl.handle.net/10356/14741 en 78 p. application/msword
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
DRNTU::Engineering::Civil engineering::Transportation
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
DRNTU::Engineering::Civil engineering::Transportation
Ong, Kai Sin.
Video analysis of vehicular flows for road traffic monitoring
description Video Analysis of Vehicular Flows for Road Traffic Monitoring” is a final year project that aims to develop a real time computer vision system that can collect traffic data, detect traffic incidents and has practical applications on intelligent traffic monitoring. Videos are sourced from Land Transport Authority (LTA) and the objectives of this project is to create a program that can detect traffic events through streaming from the IP network camera and alert the end user on the traffic conditions on the particular highway. In this report, theoretical and technical aspects of computer vision techniques are explained in detail. In theoretical aspects of computer vision techniques, techniques that will be explained in depth will be grayscaling, image differencing, edge detection and automatic thresholding. Some techniques have been implemented in the proposed system. Also, technical aspects of the prototype will be discussed. The prototype is able to retrieve images from the live streaming via the network camera and preprocess the images using image differencing. Foreground extraction is retrieved and pixel intensity is calculated by the system which serves as a guide and signal for traffic flow at the point of time. This helps to classify the congestion level.
author2 Ang Yew Hock
author_facet Ang Yew Hock
Ong, Kai Sin.
format Final Year Project
author Ong, Kai Sin.
author_sort Ong, Kai Sin.
title Video analysis of vehicular flows for road traffic monitoring
title_short Video analysis of vehicular flows for road traffic monitoring
title_full Video analysis of vehicular flows for road traffic monitoring
title_fullStr Video analysis of vehicular flows for road traffic monitoring
title_full_unstemmed Video analysis of vehicular flows for road traffic monitoring
title_sort video analysis of vehicular flows for road traffic monitoring
publishDate 2009
url http://hdl.handle.net/10356/14741
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