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Reseach Article

Image Segmentation in Computer Vision and Review of Various Segmentation Techniques

Published on August 2011 by Parita Oza
journal_cover_thumbnail
National Technical Symposium on Advancements in Computing Technologies
Foundation of Computer Science USA
NTSACT - Number 5
August 2011
Authors: Parita Oza
9fab0484-a822-423b-832a-2c655469245a

Parita Oza . Image Segmentation in Computer Vision and Review of Various Segmentation Techniques. National Technical Symposium on Advancements in Computing Technologies. NTSACT, 5 (August 2011), 29-33.

@article{
author = { Parita Oza },
title = { Image Segmentation in Computer Vision and Review of Various Segmentation Techniques },
journal = { National Technical Symposium on Advancements in Computing Technologies },
issue_date = { August 2011 },
volume = { NTSACT },
number = { 5 },
month = { August },
year = { 2011 },
issn = 0975-8887,
pages = { 29-33 },
numpages = 5,
url = { /proceedings/ntsact/number5/3214-ntst035/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Technical Symposium on Advancements in Computing Technologies
%A Parita Oza
%T Image Segmentation in Computer Vision and Review of Various Segmentation Techniques
%J National Technical Symposium on Advancements in Computing Technologies
%@ 0975-8887
%V NTSACT
%N 5
%P 29-33
%D 2011
%I International Journal of Computer Applications
Abstract

The field of computer vision is concerned with extracting information from images. The task of image segmentation is a first step in many computer vision methods and serves to simplify the problem by grouping the pixels in the image in logical ways. Image segmentation is hard to clearly define because there are many levels of detail in an image and therefore many possible ways of meaningfully grouping pixels. Many image segmentation techniques are available in the literature. Some of these techniques use only the gray level histogram, some use spatial details while others use fuzzy set theoretic approaches. The literature on color image segmentation is not that rich as it is for gray tone images. Additionally, after choosing a definition for an optimal segmentation, there are many computational difficulties in finding such segmentation. This paper critically reviews and summarizes some of these techniques. Attempts have been made to cover some clustering techniques and show sample segmentations results.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Clustering Algorithm WCSS Image Segmentation