A triple-diagonal gradient-based edge detection

Wu, Q; He, X; Hintz, T

A triple-diagonal gradient-based edge detection

Wu, Q

He, X

Hintz, T

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Publication Type:: Conference Proceeding
Citation:: IASTED International Conference on Computer Graphics and Imaging, 2003, pp. 244 - 249
Issue Date:: 2003-12-01

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Field	Value	Language
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Hintz, T	en_US
dc.date.issued	2003-12-01	en_US
dc.identifier.citation	IASTED International Conference on Computer Graphics and Imaging, 2003, pp. 244 - 249	en_US
dc.identifier.isbn	0889863768	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1716
dc.description.abstract	Gradient-based edge detection is a straightforward method to identity the edge points in the original grey-level image. It is consistent with the intuition that in the human vision system the edge points always appear where the change of grey-level is greatest within their neighbourhood. In this paper, triple-diagonal gradient-based edge detection is introduced. It is based on the features of Spiral Architecture and computes the gradients in three diagonal directions instead of approximating the gradient in one direction only as the traditional methods do. Essentially, it improves the accuracy for locating edge points. As a result, it does not need any supplementary processing to enhance the edge map.	en_US
dc.relation.ispartof	IASTED International Conference on Computer Graphics and Imaging	en_US
dc.title	A triple-diagonal gradient-based edge detection	en_US
dc.type	Conference Proceeding
utslib.for	080106 Image Processing	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Honolulu, USA	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

Gradient-based edge detection is a straightforward method to identity the edge points in the original grey-level image. It is consistent with the intuition that in the human vision system the edge points always appear where the change of grey-level is greatest within their neighbourhood. In this paper, triple-diagonal gradient-based edge detection is introduced. It is based on the features of Spiral Architecture and computes the gradients in three diagonal directions instead of approximating the gradient in one direction only as the traditional methods do. Essentially, it improves the accuracy for locating edge points. As a result, it does not need any supplementary processing to enhance the edge map.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/1716