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Conference Paper: Multiscale space vehicle component identification

TitleMultiscale space vehicle component identification
Authors
KeywordsComputers
Computer graphics
Issue Date2004
PublisherIEEE.
Citation
International Conference on Image Processing Proceedings, Singapore, 24-27 October 2004, v. 2, p. 925-928 How to Cite?
AbstractVision based vehicle recognition systems have an important role in traffic surveillance. Most of these systems however fail to distinguish vehicles with similar dimensions due to the lack of other details. This paper presents a new scale space method for identifying components of moving vehicles to enable recognition eventually. In the proposed method, vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask. It utilizes both the texture scale space and the intensity scale space to determine regions that are homogenous in texture and intensity, from which vehicle components are identified based on the relations between these regions. This method was tested on over a hundred outdoor traffic images and the results are very promising.
Persistent Identifierhttp://hdl.handle.net/10722/45775
ISSN
2020 SCImago Journal Rankings: 0.315

 

DC FieldValueLanguage
dc.contributor.authorLam, WWLen_HK
dc.contributor.authorPang, CCCen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2007-10-30T06:35:11Z-
dc.date.available2007-10-30T06:35:11Z-
dc.date.issued2004en_HK
dc.identifier.citationInternational Conference on Image Processing Proceedings, Singapore, 24-27 October 2004, v. 2, p. 925-928en_HK
dc.identifier.issn1522-4880en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45775-
dc.description.abstractVision based vehicle recognition systems have an important role in traffic surveillance. Most of these systems however fail to distinguish vehicles with similar dimensions due to the lack of other details. This paper presents a new scale space method for identifying components of moving vehicles to enable recognition eventually. In the proposed method, vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask. It utilizes both the texture scale space and the intensity scale space to determine regions that are homogenous in texture and intensity, from which vehicle components are identified based on the relations between these regions. This method was tested on over a hundred outdoor traffic images and the results are very promising.en_HK
dc.format.extent349164 bytes-
dc.format.extent10863 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectComputersen_HK
dc.subjectComputer graphicsen_HK
dc.titleMultiscale space vehicle component identificationen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1522-4880&volume=2&spage=925&epage=928&date=2004&atitle=Multiscale+space+vehicle+component+identificationen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICIP.2004.1419451en_HK
dc.identifier.hkuros102236-
dc.identifier.issnl1522-4880-

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