Linear Regression Based Global Thresholding

Aboura, K

Linear Regression Based Global Thresholding

Aboura, K

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Publisher:: BroadbandCom '09
Publication Type:: Conference Proceeding
Citation:: Selected Papers on the 4th International Conference On Broadband Communication, Information Technology & Biomedical Applications, 2009, pp. 319 - 324
Issue Date:: 2009-01

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Field	Value	Language
dc.contributor.author	Aboura, K	en_US
dc.contributor.editor	Janiczek, T	en_US
dc.contributor.editor	Klempous, R	en_US
dc.contributor.editor	Nikodem, J	en_US
dc.contributor.editor	ski, RJZ	en_US
dc.contributor.editor	Agbinya, J	en_US
dc.contributor.editor	Braun, R	en_US
dc.contributor.editor	Chaczko, Z	en_US
dc.date	2009-07-15	en_US
dc.date.issued	2009-01	en_US
dc.identifier.citation	Selected Papers on the 4th International Conference On Broadband Communication, Information Technology & Biomedical Applications, 2009, pp. 319 - 324	en_US
dc.identifier.isbn	978-83-7493-470-1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11182
dc.description.abstract	A large number of thresholding methods exist. These methods perform differently in various image analysis problems where they are often used locally. They are not as effective globally. Global thresholding is a difficult task in most problems. We highlight a linear regression based global thresholding method that performed well in an engineering problem. This same approach can be used in biomedical applications where the environment is better controlled.	en_US
dc.publisher	BroadbandCom '09	en_US
dc.relation.ispartof	Selected Papers on the 4th International Conference On Broadband Communication, Information Technology & Biomedical Applications	en_US
dc.relation.ispartof	International Conference of Broadband Communication, Information Technology and Biomedical Applications	en_US
dc.title	Linear Regression Based Global Thresholding	en_US
dc.type	Conference Proceeding
utslib.location	Wroclaw, Poland	en_US
utslib.location.activity	Wroclaw, Poland	en_US
utslib.for	100502 Broadband and Modem Technology	en_US
dc.location.activity	Wroclaw, Poland	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 Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	Wroclaw, Poland	en_US
pubs.start-date	2009-07-15	en_US

Abstract:

A large number of thresholding methods exist. These methods perform differently in various image analysis problems where they are often used locally. They are not as effective globally. Global thresholding is a difficult task in most problems. We highlight a linear regression based global thresholding method that performed well in an engineering problem. This same approach can be used in biomedical applications where the environment is better controlled.

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

http://hdl.handle.net/10453/11182