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Reseach Article

An Intelligent Video Surveillance Framework with Big Data Management for Indian Road Traffic System

by R. Balaji Ganesh, S. Appavu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 10
Year of Publication: 2015
Authors: R. Balaji Ganesh, S. Appavu
10.5120/ijca2015905519

R. Balaji Ganesh, S. Appavu . An Intelligent Video Surveillance Framework with Big Data Management for Indian Road Traffic System. International Journal of Computer Applications. 123, 10 ( August 2015), 12-19. DOI=10.5120/ijca2015905519

@article{ 10.5120/ijca2015905519,
author = { R. Balaji Ganesh, S. Appavu },
title = { An Intelligent Video Surveillance Framework with Big Data Management for Indian Road Traffic System },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 10 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 12-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number10/21994-2015905519/ },
doi = { 10.5120/ijca2015905519 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:12:19.776249+05:30
%A R. Balaji Ganesh
%A S. Appavu
%T An Intelligent Video Surveillance Framework with Big Data Management for Indian Road Traffic System
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 10
%P 12-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Intelligent Transportation Systems (ITS) and Advanced Traveller Information Systems (ATIS) are the emerging areas of research. They focus with keen interest to solve the issues in traffic management and planning and designing infrastructure to meet the demanding needs of the general public. Many research articles focus on developing video surveillance algorithms for processing video data captured at real-time traffic scenes, but as there is a huge demand for more sophisticated software systems, complexity of the algorithms gets increased in terms of data storage and large scale processing. This research article focuses on refining a framework for large scale video analytics while incorporating the simple, light-weight aspects of a video surveillance algorithm, and makes an insight by adopting blob tracking based video surveillance algorithm for large scale video analytics. The proposed system uses hadoop’ map-reduce function to clean and pre-process the hours of traffic video captured in the local site stores. It summarizes and transmits the key frames of the video data to the central computing server to analyses the video frames. The key frame differencing method has been justified as a pronouncing method for data preprocessing and cleaning. Further this system follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

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Index Terms

Computer Science
Information Sciences

Keywords

Large scale video analytics Road traffic surveillance system Blob detection Traffic density estimation Video Systems and Analytics Intelligent Video Systems (IVS) in big data