Parallel edge detection on a virtual hexagonal structure

He, X; Jia, W; Wu, Q; Hintz, T

Parallel edge detection on a virtual hexagonal structure

He, X

Jia, W

Wu, Q

Hintz, T

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, 4459 LNCS pp. 751 - 756
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Jia, W https://orcid.org/0000-0002-0940-3338	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	Hintz, T	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, 4459 LNCS pp. 751 - 756	en_US
dc.identifier.isbn	9783540723592	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/4944
dc.description.abstract	This paper presents an edge detection method based on bilateral filtering taking into account both spatial closeness and intensity similarity of pixels in order to preserve important visual cues provided by edges and reduce the sharpness of transitions in intensity values as well. In addition, the edge detection method proposed in this paper is achieved on sampled images represented on a newly developed virtual hexagonal structure. Due to the compact and circular nature of the hexagonal lattice, a better quality edge map is obtained. We also present a parallel implementation for edge detection on the virtual hexagonal structure that significantly increases the computation speed. © Springer-Verlag Berlin Heidelberg 2007.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0451666
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Parallel edge detection on a virtual hexagonal structure	en_US
dc.type	Conference Proceeding
utslib.citation.volume	4459 LNCS	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Paris, France	en_US
dc.location.activity	Univ Arizona, Tucson, AZ
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	closed_access
pubs.publication-status	Published	en_US
pubs.volume	4459 LNCS	en_US

Abstract:

This paper presents an edge detection method based on bilateral filtering taking into account both spatial closeness and intensity similarity of pixels in order to preserve important visual cues provided by edges and reduce the sharpness of transitions in intensity values as well. In addition, the edge detection method proposed in this paper is achieved on sampled images represented on a newly developed virtual hexagonal structure. Due to the compact and circular nature of the hexagonal lattice, a better quality edge map is obtained. We also present a parallel implementation for edge detection on the virtual hexagonal structure that significantly increases the computation speed. © Springer-Verlag Berlin Heidelberg 2007.

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http://hdl.handle.net/10453/4944