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Reseach Article

Performance Analysis of Segmentation Techniques

by Amandeep Singh, Jaspinder Sidhu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 23
Year of Publication: 2012
Authors: Amandeep Singh, Jaspinder Sidhu
10.5120/7088-9758

Amandeep Singh, Jaspinder Sidhu . Performance Analysis of Segmentation Techniques. International Journal of Computer Applications. 45, 23 ( May 2012), 18-23. DOI=10.5120/7088-9758

@article{ 10.5120/7088-9758,
author = { Amandeep Singh, Jaspinder Sidhu },
title = { Performance Analysis of Segmentation Techniques },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 23 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 18-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number23/7088-9758/ },
doi = { 10.5120/7088-9758 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:38:20.093969+05:30
%A Amandeep Singh
%A Jaspinder Sidhu
%T Performance Analysis of Segmentation Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 23
%P 18-23
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This article presents the performance analysis of different segmentation techniques. Global thresholding, Adaptive thresholding, Region grow and Active contour using level set techniques has been used in this paper for proposed segmentation analysis. In this procedure flows as first by Appling segmentation technique to extract ROI from image and calculate the parameters from the resulting image obtained by the applied techniques. Parameters are PSNR and MSE. Segmentation techniques have been tested on medical and synthetic data sets and results are compared with each other. Tests indicate that using level set contour significantly improves the ability of extracting region of interest with unbroken boundaries and Adaptive thresholding acquires most of the details present in the image. Global thresholding have the highest success rate of extracting the region of interest

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Index Terms

Computer Science
Information Sciences

Keywords

Global Threshold Adaptive Threshold Region Grow Level Set Contour Hybrid Segmentation