A skeleton algorithm on clusters for image edge detection

He, X; Hintz, T; Wu, Q

A skeleton algorithm on clusters for image edge detection

He, X

Hintz, T Wu, Q

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 15th International Parallel and Distributed Processing Symposium, IPDPS 2001, 2001, pp. 1359 - 1364
Issue Date:: 2001-01-01

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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	2001-01-01	en_US
dc.identifier.citation	Proceedings - 15th International Parallel and Distributed Processing Symposium, IPDPS 2001, 2001, pp. 1359 - 1364	en_US
dc.identifier.isbn	0769509908	en_US
dc.identifier.isbn	9780769509907	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2743
dc.description.abstract	© 2001 IEEE. Image edge detection in computer vision and image processing is a process which detects one kind of significant feature in an image that appears as large delta values in intensities. In this paper, a parallel algorithmic skeleton for edge detection is proposed based on the Spiral Architecture and the Gaussian multi-scale theory. UNIX-based network programming mechanisms in C are used for the implementation on a cluster of Sun-workstations. Our work provides an efficient algorithm for edge detection and is robust to noise.	en_US
dc.relation.ispartof	Proceedings - 15th International Parallel and Distributed Processing Symposium, IPDPS 2001	en_US
dc.relation.isbasedon	10.1109/IPDPS.2001.925114	en_US
dc.title	A skeleton algorithm on clusters for image edge detection	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	San Francisco, 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	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2001 IEEE. Image edge detection in computer vision and image processing is a process which detects one kind of significant feature in an image that appears as large delta values in intensities. In this paper, a parallel algorithmic skeleton for edge detection is proposed based on the Spiral Architecture and the Gaussian multi-scale theory. UNIX-based network programming mechanisms in C are used for the implementation on a cluster of Sun-workstations. Our work provides an efficient algorithm for edge detection and is robust to noise.

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http://hdl.handle.net/10453/2743