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Comparison of Traditional Approach for Edge Detection with Soft Computing Approach

by Neha S. Joshi, Nitin S. Choubey
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 96 - Number 11
Year of Publication: 2014
Authors: Neha S. Joshi, Nitin S. Choubey
10.5120/16837-6683

Neha S. Joshi, Nitin S. Choubey . Comparison of Traditional Approach for Edge Detection with Soft Computing Approach. International Journal of Computer Applications. 96, 11 ( June 2014), 17-23. DOI=10.5120/16837-6683

@article{ 10.5120/16837-6683,
author = { Neha S. Joshi, Nitin S. Choubey },
title = { Comparison of Traditional Approach for Edge Detection with Soft Computing Approach },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 96 },
number = { 11 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 17-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume96/number11/16837-6683/ },
doi = { 10.5120/16837-6683 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:21:28.209458+05:30
%A Neha S. Joshi
%A Nitin S. Choubey
%T Comparison of Traditional Approach for Edge Detection with Soft Computing Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 96
%N 11
%P 17-23
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image processing supports applications in different fields such as medicine, astronomy, product quality, industrial applications. Edge detection plays important role in segmentation and object identification process. Soft computing approach represents a good mathematical framework to deal with uncertainty of information. The performance of the well-known edge detectors, like Canny, Sobel, etc, depends critically on the choice of the input parameters. Threshold decision is the key uncertainty in the edge detection algorithms. In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical morphology and multiscale wavelet transform is proposed. The proposed method overcomes the limitation of wavelet based edge detection and mathematical morphology based edge detection in noisy images. Method present will give best results for noisy images.

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Index Terms

Computer Science
Information Sciences

Keywords

Edge detection Wavelet transform Mathematical morphology Fuzzy logic

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