Feature enhancement using gradient salience on thermal image

Li, Z; Zhang, J; Wu, Q; Geers, G

Feature enhancement using gradient salience on thermal image

Li, Z Zhang, J

Wu, Q

Geers, G

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010, 2010, pp. 556 - 562
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Li, Z	en_US
dc.contributor.author	Zhang, J https://orcid.org/0000-0002-7240-3541	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	Geers, G	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010, 2010, pp. 556 - 562	en_US
dc.identifier.isbn	9780769542713	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16109
dc.description.abstract	Feature enhancement in an image is to reinforce some exacted features so that it can be used for object classification and detection. As the thermal image is lack of texture and colorful information, the techniques for visual image feature enhancement is insufficient to apply to thermal images. In this paper, we propose a new gradient-based approach for feature enhancement in thermal image. We use the statistical properties of gradient of foreground object profiles, and formulate object features with gradient saliency. Empirical evaluation of the proposed approach shows significant performance improved on human contours which can be used for detection and classification. © 2010 IEEE.	en_US
dc.relation.ispartof	Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010	en_US
dc.relation.isbasedon	10.1109/DICTA.2010.99	en_US
dc.title	Feature enhancement using gradient salience on thermal image	en_US
dc.type	Conference Proceeding
utslib.for	080106 Image Processing	en_US
dc.location.activity	Sydney, Australia	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 - 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:

Feature enhancement in an image is to reinforce some exacted features so that it can be used for object classification and detection. As the thermal image is lack of texture and colorful information, the techniques for visual image feature enhancement is insufficient to apply to thermal images. In this paper, we propose a new gradient-based approach for feature enhancement in thermal image. We use the statistical properties of gradient of foreground object profiles, and formulate object features with gradient saliency. Empirical evaluation of the proposed approach shows significant performance improved on human contours which can be used for detection and classification. © 2010 IEEE.

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http://hdl.handle.net/10453/16109