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Object Matching using Skeletonization based on Hamming Distance

by M. Sankari, C. Meena
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 28 - Number 7
Year of Publication: 2011
Authors: M. Sankari, C. Meena
10.5120/3396-4724

M. Sankari, C. Meena . Object Matching using Skeletonization based on Hamming Distance. International Journal of Computer Applications. 28, 7 ( August 2011), 46-50. DOI=10.5120/3396-4724

@article{ 10.5120/3396-4724,
author = { M. Sankari, C. Meena },
title = { Object Matching using Skeletonization based on Hamming Distance },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 28 },
number = { 7 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 46-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume28/number7/3396-4724/ },
doi = { 10.5120/3396-4724 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:14:11.513329+05:30
%A M. Sankari
%A C. Meena
%T Object Matching using Skeletonization based on Hamming Distance
%J International Journal of Computer Applications
%@ 0975-8887
%V 28
%N 7
%P 46-50
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Identification of an object from a dynamic background is a challenging process in computer vision and pattern matching research. The proposed algorithm identifies moving objects from the sequence of video frames which contains dynamically changing backgrounds in the noisy environment. In connection with our previous work, here we have proposed a methodology to perform skeletanization of an object and identifies it. The recent vehicle recognition methods could fail to recognize an object and produce more false acceptance rate(FAR) or false rejection rate (FRR). This paper recommends a method for object identification using weighted distance to extract features. Experimental results and comparisons using real data demonstrate the pre-eminence of the proposed approach.

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Index Terms

Computer Science
Information Sciences

Keywords

Distance transformations false acceptance rate false rejection rate Skeletanization Traffic video sequences weighted distance

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