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Edge Detection using Moore Neighborhood

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 61 - Number 3
Year of Publication: 2013
Authors:
Pratibha Sharma
Manoj Diwakar
Niranjan Lal
10.5120/9910-4506

Pratibha Sharma, Manoj Diwakar and Niranjan Lal. Article: Edge Detection using Moore Neighborhood. International Journal of Computer Applications 61(3):26-30, January 2013. Full text available. BibTeX

@article{key:article,
	author = {Pratibha Sharma and Manoj Diwakar and Niranjan Lal},
	title = {Article: Edge Detection using Moore Neighborhood},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {61},
	number = {3},
	pages = {26-30},
	month = {January},
	note = {Full text available}
}

Abstract

Edge detection is a fundamental tool in image processing. Several edge detectors have been proposed in literature for enhancing and detecting edges in images. Image Edge detection significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. In this paper, the application of two-dimensional cellular automata using Moore Neighborhood has been proposed for edge detection. The idea is simple but effective technique for edge detection. Edge basically occurs where there is significant change in intensity. The principle of the algorithm used is to increase the difference between those pixels where intensity values change significantly. So by using this concept, detected edges are wider and clear. The given algorithm can be applied to gray scale and monochrome images.

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