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Article: Highly accurate texture-based vehicle segmentation method

TitleHighly accurate texture-based vehicle segmentation method
Authors
KeywordsIntelligent transportation systems
Shadow detection
Texture analysis
Vehicle segmentation
Visual traffic surveillance
Issue Date2004
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oe
Citation
Optical Engineering, 2004, v. 43 n. 3, p. 591-603 How to Cite?
AbstractIn modern traffic surveillance, computer vision methods have often been employed to detect vehicles of interest because of the rich information content contained in an image. Segmentation of moving vehicles using image processing and analysis algorithms has been an important research topic in the past decade. However, segmentation results are strongly affected by two issues: moving cast shadows and reflective regions, both of which reduce accuracy and require postprocessing to alleviate the degradation. We propose an efficient and highly accurate texture-based method for extracting the boundary of vehicles from the stationary background that is free from the effect of moving cast shadows and reflective regions. The segmentation method utilizes the differences in textural property between the road, vehicle cast shadow, reflection on the vehicle, and the vehicle itself, rather than just the intensity differences between them. By further combining the luminance and chrominance properties into an OR map, a number of foreground vehicle masks are constructed through a series of morphological operations, where each mask describes the outline of a moving vehicle. The proposed method has been tested on real-world traffic image sequences and achieved an average error rate of 3.44% for 50 tested vehicle images. © 2004 Society of Photo-Optical Instrumentation Engineers.
Persistent Identifierhttp://hdl.handle.net/10722/42977
ISSN
2015 Impact Factor: 0.984
2015 SCImago Journal Rankings: 0.485
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLam, WWLen_HK
dc.contributor.authorPang, CCCen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2007-03-23T04:35:54Z-
dc.date.available2007-03-23T04:35:54Z-
dc.date.issued2004en_HK
dc.identifier.citationOptical Engineering, 2004, v. 43 n. 3, p. 591-603en_HK
dc.identifier.issn0091-3286en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42977-
dc.description.abstractIn modern traffic surveillance, computer vision methods have often been employed to detect vehicles of interest because of the rich information content contained in an image. Segmentation of moving vehicles using image processing and analysis algorithms has been an important research topic in the past decade. However, segmentation results are strongly affected by two issues: moving cast shadows and reflective regions, both of which reduce accuracy and require postprocessing to alleviate the degradation. We propose an efficient and highly accurate texture-based method for extracting the boundary of vehicles from the stationary background that is free from the effect of moving cast shadows and reflective regions. The segmentation method utilizes the differences in textural property between the road, vehicle cast shadow, reflection on the vehicle, and the vehicle itself, rather than just the intensity differences between them. By further combining the luminance and chrominance properties into an OR map, a number of foreground vehicle masks are constructed through a series of morphological operations, where each mask describes the outline of a moving vehicle. The proposed method has been tested on real-world traffic image sequences and achieved an average error rate of 3.44% for 50 tested vehicle images. © 2004 Society of Photo-Optical Instrumentation Engineers.en_HK
dc.format.extent1134085 bytes-
dc.format.extent5183 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oeen_HK
dc.relation.ispartofOptical Engineeringen_HK
dc.rightsCopyright 2004 Society of Photo-Optical Instrumentation Engineers. This paper was published in Optical Engineering, 2004, v. 43 n. 3, p. 591-603 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectIntelligent transportation systemsen_HK
dc.subjectShadow detectionen_HK
dc.subjectTexture analysisen_HK
dc.subjectVehicle segmentationen_HK
dc.subjectVisual traffic surveillanceen_HK
dc.titleHighly accurate texture-based vehicle segmentation methoden_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0091-3286&volume=43&issue=3&spage=591&epage=603&date=2004&atitle=Highly+accurate+texture-based+vehicle+segmentation+methoden_HK
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/1.1645849en_HK
dc.identifier.scopuseid_2-s2.0-2342650830en_HK
dc.identifier.hkuros91670-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-2342650830&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume43en_HK
dc.identifier.issue3en_HK
dc.identifier.spage591en_HK
dc.identifier.epage603en_HK
dc.identifier.isiWOS:000220552400009-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLam, WWL=16836339900en_HK
dc.identifier.scopusauthoridPang, CCC=7201425202en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK

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