Image partitioning on spiral architecture

Wu, Q; He, X

Image partitioning on spiral architecture

Wu, Q

He, X

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Publication Type:: Chapter
Citation:: The Handbook of Research on Scalable Computing Technologies, 2009, 2 pp. 808 - 840
Issue Date:: 2009-12-01

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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.date.issued	2009-12-01	en_US
dc.identifier.citation	The Handbook of Research on Scalable Computing Technologies, 2009, 2 pp. 808 - 840	en_US
dc.identifier.isbn	9781605666617	en_US
dc.identifier.uri	http://hdl.handle.net/10453/12972
dc.description.abstract	Spiral Architecture is a relatively new and powerful approach to image processing. It contains very useful geometric and algebraic properties. Based on the abundant research achievements in the past decades, it is shown that Spiral Architecture will play an increasingly important role in image processing and computer vision. This chapter presents a significant application of Spiral Architecture for distributed image processing. It demonstrates the impressive characteristics of spiral architecture for high performance image processing. The proposed method tackles several challenging practical problems during the implementation. The proposed method reduces the data communication between the processing nodes and is configurable. Moreover, the proposed partitioning scheme has a consistent approach: after image partitioning each sub-image should be a representative of the original one without changing the basic object, which is important to the related image processing operations. © 2010, IGI Global.	en_US
dc.relation.ispartof	The Handbook of Research on Scalable Computing Technologies	en_US
dc.relation.isbasedon	10.4018/978-1-60566-661-7.ch035	en_US
dc.title	Image partitioning on spiral architecture	en_US
dc.type	Chapter
utslib.citation.volume	2	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/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	2	en_US

Abstract:

Spiral Architecture is a relatively new and powerful approach to image processing. It contains very useful geometric and algebraic properties. Based on the abundant research achievements in the past decades, it is shown that Spiral Architecture will play an increasingly important role in image processing and computer vision. This chapter presents a significant application of Spiral Architecture for distributed image processing. It demonstrates the impressive characteristics of spiral architecture for high performance image processing. The proposed method tackles several challenging practical problems during the implementation. The proposed method reduces the data communication between the processing nodes and is configurable. Moreover, the proposed partitioning scheme has a consistent approach: after image partitioning each sub-image should be a representative of the original one without changing the basic object, which is important to the related image processing operations. © 2010, IGI Global.

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http://hdl.handle.net/10453/12972