Automatically detecting road sign text from natural scene video

Jia, W; He, X; Tien, D

Automatically detecting road sign text from natural scene video

Jia, W

He, X

Tien, D

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Publication Type:: Conference Proceeding
Citation:: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2006
Issue Date:: 2006-01-01

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Field	Value	Language
dc.contributor.author	Jia, W https://orcid.org/0000-0002-0940-3338	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Tien, D	en_US
dc.date.issued	2006-01-01	en_US
dc.identifier.citation	IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2006	en_US
dc.identifier.isbn	1424405491	en_US
dc.identifier.isbn	9781424405497	en_US
dc.identifier.issn	2159-3442	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2594
dc.description.abstract	Automatic detection of text on road signs can help drivers keep aware of the traffic situation and surrounding environments by reminding them of the signs ahead. Current systems can only detect constrained road signs or produce unsatisfying performance when dealing with complex scenes in practical use. This paper firstly reviews the existing techniques used for text detection from natural scene. A novel system which detects text on road signs from natural scene video is then proposed. Our detailed approaches and methodology give a promising solution to this problem in order to reduce the running time and improve the recognition rate. © 2006 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0451666
dc.relation.ispartof	IEEE Region 10 Annual International Conference, Proceedings/TENCON	en_US
dc.relation.isbasedon	10.1109/TENCON.2006.343914	en_US
dc.title	Automatically detecting road sign text from natural scene video	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	Hong Kiong	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
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

Automatic detection of text on road signs can help drivers keep aware of the traffic situation and surrounding environments by reminding them of the signs ahead. Current systems can only detect constrained road signs or produce unsatisfying performance when dealing with complex scenes in practical use. This paper firstly reviews the existing techniques used for text detection from natural scene. A novel system which detects text on road signs from natural scene video is then proposed. Our detailed approaches and methodology give a promising solution to this problem in order to reduce the running time and improve the recognition rate. © 2006 IEEE.

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http://hdl.handle.net/10453/2594