Distributed image processing on spiral architecture

Wu, Q; He, X; Hintz, T

Distributed image processing on spiral architecture

Wu, Q

He, X

Hintz, T

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 5th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2002, 2002, pp. 84 - 91
Issue Date:: 2002-01-01

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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	2002-01-01	en_US
dc.identifier.citation	Proceedings - 5th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2002, 2002, pp. 84 - 91	en_US
dc.identifier.isbn	0769515126	en_US
dc.identifier.isbn	9780769515120	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2343
dc.description.abstract	© 2002 IEEE. Improving computation efficiency is a key issue in image processing, especially in edge detection, which is very computationally intensive. With the development of real-time applications of image processing, fast processing response is becoming more critical. In this paper, a technique for distributed image processing on a spiral architecture is proposed, which provides a platform for speeding up image processing based on clusters.	en_US
dc.relation.ispartof	Proceedings - 5th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2002	en_US
dc.relation.isbasedon	10.1109/ICAPP.2002.1173556	en_US
dc.title	Distributed image processing on spiral architecture	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	Beijing, China	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	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2002 IEEE. Improving computation efficiency is a key issue in image processing, especially in edge detection, which is very computationally intensive. With the development of real-time applications of image processing, fast processing response is becoming more critical. In this paper, a technique for distributed image processing on a spiral architecture is proposed, which provides a platform for speeding up image processing based on clusters.

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

http://hdl.handle.net/10453/2343