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Article: An efficient parameterless quadrilateral-based image segmentation method

TitleAn efficient parameterless quadrilateral-based image segmentation method
Authors
KeywordsApproximate methods
Object representations
Quadrilateral-based segmentation
Region growing
Issue Date2005
PublisherIEEE. The Journal's web site is located at http://www.computer.org/tpami
Citation
IEEE Transactions On Pattern Analysis And Machine Intelligence, 2005, v. 27 n. 9, p. 1446-1458 How to Cite?
AbstractThis paper proposes a general quadrilateral-based framework for image segmentation, in which quadrilaterals are first constructed from an edge map, where neighboring quadrilaterals with similar features of interest are then merged together to form regions. Under the proposed framework, the quadrilaterals enable the elimination of local variations and unnecessary details for merging from which each segmented region is accurately and completely described by a set of quadrilaterals. To illustrate the effectiveness of the proposed framework, we derived an efficient and high-performance parameterless quadrilateral-based segmentation algorithm from the framework. The proposed algorithm shows that the regions obtained under the framework are segmented into multiple levels of quadrilaterals that accurately represent the regions without severely over or undersegmenting them. When evaluated objectively and subjectively, the proposed algorithm performs better than three other segmentation techniques, namely, seeded region growing, K-means clustering and constrained gravitational clustering, and offers an efficient description of the segmented objects conducive to content-based applications. © 2005 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/44731
ISSN
2015 Impact Factor: 6.077
2015 SCImago Journal Rankings: 7.653
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChung, RHYen_HK
dc.contributor.authorYung, NHCen_HK
dc.contributor.authorCheung, PYSen_HK
dc.date.accessioned2007-10-30T06:08:58Z-
dc.date.available2007-10-30T06:08:58Z-
dc.date.issued2005en_HK
dc.identifier.citationIEEE Transactions On Pattern Analysis And Machine Intelligence, 2005, v. 27 n. 9, p. 1446-1458en_HK
dc.identifier.issn0162-8828en_HK
dc.identifier.urihttp://hdl.handle.net/10722/44731-
dc.description.abstractThis paper proposes a general quadrilateral-based framework for image segmentation, in which quadrilaterals are first constructed from an edge map, where neighboring quadrilaterals with similar features of interest are then merged together to form regions. Under the proposed framework, the quadrilaterals enable the elimination of local variations and unnecessary details for merging from which each segmented region is accurately and completely described by a set of quadrilaterals. To illustrate the effectiveness of the proposed framework, we derived an efficient and high-performance parameterless quadrilateral-based segmentation algorithm from the framework. The proposed algorithm shows that the regions obtained under the framework are segmented into multiple levels of quadrilaterals that accurately represent the regions without severely over or undersegmenting them. When evaluated objectively and subjectively, the proposed algorithm performs better than three other segmentation techniques, namely, seeded region growing, K-means clustering and constrained gravitational clustering, and offers an efficient description of the segmented objects conducive to content-based applications. © 2005 IEEE.en_HK
dc.format.extent2238312 bytes-
dc.format.extent1797 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE. The Journal's web site is located at http://www.computer.org/tpamien_HK
dc.relation.ispartofIEEE Transactions on Pattern Analysis and Machine Intelligenceen_HK
dc.rights©2005 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.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectApproximate methodsen_HK
dc.subjectObject representationsen_HK
dc.subjectQuadrilateral-based segmentationen_HK
dc.subjectRegion growingen_HK
dc.subject.meshAlgorithms-en_HK
dc.subject.meshArtificial-Intelligenceen_HK
dc.subject.meshImage-Enhancement-methodsen_HK
dc.subject.meshImage-Interpretation,-Computer-Assisted-methodsen_HK
dc.subject.meshImaging,-Three-Dimensional-methodsen_HK
dc.titleAn efficient parameterless quadrilateral-based image segmentation methoden_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0162-8828&volume=27&issue=9&spage=1446&epage=1458&date=2005&atitle=An+efficient+parameterless+quadrilateral-based+image+segmentation+methoden_HK
dc.identifier.emailChung, RHY:hychung@cs.hku.hken_HK
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_HK
dc.identifier.emailCheung, PYS:paul.cheung@hku.hken_HK
dc.identifier.authorityChung, RHY=rp00219en_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.identifier.authorityCheung, PYS=rp00077en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TPAMI.2005.171en_HK
dc.identifier.pmid16173187en_HK
dc.identifier.scopuseid_2-s2.0-25844500310en_HK
dc.identifier.hkuros100932-
dc.identifier.hkuros122309-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-25844500310&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume27en_HK
dc.identifier.issue9en_HK
dc.identifier.spage1446en_HK
dc.identifier.epage1458en_HK
dc.identifier.isiWOS:000230463300007-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChung, RHY=14059962600en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK
dc.identifier.scopusauthoridCheung, PYS=7202595335en_HK

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