Gradient-Based Edge Detection on a Hexagonal Structure

He, S; Wu, Q; Hintz, TB; Jia, W

Gradient-Based Edge Detection on a Hexagonal Structure

He, S

Wu, Q

Hintz, TB Jia, W

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Publisher:: Institute of Business Administration
Publication Type:: Journal Article
Citation:: Business Review, 2008, 3 (1), pp. 133 - 143
Issue Date:: 2008-01

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Field	Value	Language
dc.contributor.author	He, S https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	Hintz, TB	en_US
dc.contributor.author	Jia, W https://orcid.org/0000-0002-0940-3338	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	Business Review, 2008, 3 (1), pp. 133 - 143	en_US
dc.identifier.issn	1990-6587	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8918
dc.identifier.uri	http://hdl.handle.net/10453/34158
dc.description.abstract	Gradient-based edge detection is a straightforward method to identify the edge points in the original grey-level image. It is intuitive that in the human vision system the edge points always appear where the grey-level value is greatly changed. Spiral Architecture is a relatively new image data structure that is inspired from anatomical considerations of the primate's vision. In Spiral Architecture, each image is represented as a collection of hexagonal pixels. Edge detection on Spiral Architecture has features of fast computation and accurate localization. In this paper, we present and compare gradient-based edge detection algorithms on Spiral Architecture. The experimental results show that the edge detection on Spiral Architecture outperforms that on traditional square image structure.	en_US
dc.publisher	Institute of Business Administration	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0451666
dc.relation.ispartof	Business Review	en_US
dc.relation.isbasedon	10.1109/ICARCV.2008.4795633	en_US
dc.title	Gradient-Based Edge Detection on a Hexagonal Structure	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	3	en_US
utslib.for	080106 Image Processing	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	080109 Pattern Recognition and Data Mining	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.consider-herdc	true	en_US
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	3	en_US

Abstract:

Gradient-based edge detection is a straightforward method to identify the edge points in the original grey-level image. It is intuitive that in the human vision system the edge points always appear where the grey-level value is greatly changed. Spiral Architecture is a relatively new image data structure that is inspired from anatomical considerations of the primate's vision. In Spiral Architecture, each image is represented as a collection of hexagonal pixels. Edge detection on Spiral Architecture has features of fast computation and accurate localization. In this paper, we present and compare gradient-based edge detection algorithms on Spiral Architecture. The experimental results show that the edge detection on Spiral Architecture outperforms that on traditional square image structure.

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http://hdl.handle.net/10453/8918