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Reseach Article

A Survey on Image Segmentation Techniques for Edge Detection

Published on March 2013 by K. S. Selvanayaki, R. M. Somasundaram
International Conference on Innovation in Communication, Information and Computing 2013
Foundation of Computer Science USA
ICICIC2013 - Number 2
March 2013
Authors: K. S. Selvanayaki, R. M. Somasundaram
dc6ba489-ee60-4aa2-9d5d-44ffe837b71a

K. S. Selvanayaki, R. M. Somasundaram . A Survey on Image Segmentation Techniques for Edge Detection. International Conference on Innovation in Communication, Information and Computing 2013. ICICIC2013, 2 (March 2013), 31-34.

@article{
author = { K. S. Selvanayaki, R. M. Somasundaram },
title = { A Survey on Image Segmentation Techniques for Edge Detection },
journal = { International Conference on Innovation in Communication, Information and Computing 2013 },
issue_date = { March 2013 },
volume = { ICICIC2013 },
number = { 2 },
month = { March },
year = { 2013 },
issn = 0975-8887,
pages = { 31-34 },
numpages = 4,
url = { /proceedings/icicic2013/number2/11297-1391/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Innovation in Communication, Information and Computing 2013
%A K. S. Selvanayaki
%A R. M. Somasundaram
%T A Survey on Image Segmentation Techniques for Edge Detection
%J International Conference on Innovation in Communication, Information and Computing 2013
%@ 0975-8887
%V ICICIC2013
%N 2
%P 31-34
%D 2013
%I International Journal of Computer Applications
Abstract

Images in real world can be categorized based on the mode of capture, information, type i,e nature ,flowers etc. This is of vital importance as the user is interested in retrieving information specific to the category. The images need to be segmented in complex scene for providing the appropriate information. This leads to lot of challenges in real time. This paper presents a complete survey of different image segmentation techniques that are available. The paper offers suggestions for selecting the appropriate technique for segmenting the images based on the different performance parameters. A complete tabulation of the different segmentation techniques analyzed has been presented at the end of the paper. The segmentation techniques has been analyzed considering the edge detection as a vital factor. The paper also provides research directions for using neural approaches for segmentation.

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Index Terms

Computer Science
Information Sciences

Keywords

Edge Feature Vector Neural Network Segmentation Training Function