Edge detection on spiral architecture: An overview

He, X; Hintz, T; Wu, Q

Edge detection on spiral architecture: An overview

He, X

Hintz, T Wu, Q

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, PDPTA'04, 2004, 1 pp. 406 - 412
Issue Date:: 2004-12-01

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Field	Value	Language
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Hintz, T	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.date.issued	2004-12-01	en_US
dc.identifier.citation	Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, PDPTA'04, 2004, 1 pp. 406 - 412	en_US
dc.identifier.isbn	1932415262	en_US
dc.identifier.isbn	9781932415261	en_US
dc.identifier.uri	http://hdl.handle.net/10453/6960
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 greylevel 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 briefly review the edge detection methods on Spiral Architecture including the edge focusing technique, bilateral filter, and triple-diagonal gradient. Parallel algorithms for edge detection will be discussed. We will also list problems for future work.	en_US
dc.relation.ispartof	Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, PDPTA'04	en_US
dc.title	Edge detection on spiral architecture: An overview	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1	en_US
utslib.for	0805 Distributed Computing	en_US
dc.location.activity	Las Vegas, 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
pubs.volume	1	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 greylevel 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 briefly review the edge detection methods on Spiral Architecture including the edge focusing technique, bilateral filter, and triple-diagonal gradient. Parallel algorithms for edge detection will be discussed. We will also list problems for future work.

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http://hdl.handle.net/10453/6960