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Reseach Article

Intelligent Video Surveillance System based on Wavelet Transform and Support Vector Machine

by Meghana M. Deshpande, Jaideep G. Rana
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 14
Year of Publication: 2012
Authors: Meghana M. Deshpande, Jaideep G. Rana
10.5120/7419-0453

Meghana M. Deshpande, Jaideep G. Rana . Intelligent Video Surveillance System based on Wavelet Transform and Support Vector Machine. International Journal of Computer Applications. 48, 14 ( June 2012), 42-45. DOI=10.5120/7419-0453

@article{ 10.5120/7419-0453,
author = { Meghana M. Deshpande, Jaideep G. Rana },
title = { Intelligent Video Surveillance System based on Wavelet Transform and Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 14 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 42-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number14/7419-0453/ },
doi = { 10.5120/7419-0453 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:44:05.098316+05:30
%A Meghana M. Deshpande
%A Jaideep G. Rana
%T Intelligent Video Surveillance System based on Wavelet Transform and Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 14
%P 42-45
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automatic human detection is an important application where security is the main concern. As human detection problem involves classification of two objects as humans and others, a human detection using intelligent video surveillance system is presented using support vector machine to detect human in surveillance field. In this paper, in order to improve the efficiency of the machine learning 2D Wavelet transform based features are used. It consists of wavelet statistical features and wavelet co-occurrence features which are obtained from red, green and blue layers of sample images. The sample images are obtained through the video which forms training input to SVM. The experimental results demonstrate that the proposed system achieves good success rate for wavelet co-occurrence features.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Human Detection Support Vector Machine Video Surveillance Wavelet Transform