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Comparison of Traditional Approach for Edge Detection with Soft Computing Approach

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 11
Year of Publication: 2014
Authors:
Neha S. Joshi
Nitin S. Choubey
10.5120/16837-6683

Neha S Joshi and Nitin S Choubey. Article: Comparison of Traditional Approach for Edge Detection with Soft Computing Approach. International Journal of Computer Applications 96(11):17-23, June 2014. Full text available. BibTeX

@article{key:article,
	author = {Neha S. Joshi and Nitin S. Choubey},
	title = {Article: Comparison of Traditional Approach for Edge Detection with Soft Computing Approach},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {11},
	pages = {17-23},
	month = {June},
	note = {Full text available}
}

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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