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Article: Deformable contours: Modeling and extraction

TitleDeformable contours: Modeling and extraction
Authors
KeywordsMarkov processes
Mathematical models
Mathematical transformations
Matrix algebra
Issue Date1995
PublisherI E E E. The Journal's web site is located at http://www.computer.org/tpami
Citation
Ieee Transactions On Pattern Analysis And Machine Intelligence, 1995, v. 17 n. 11, p. 1084-1090 How to Cite?
AbstractThis paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local deformations, this yields prior distribution that exerts influence over a global model while allowing for deformations. We then cast the problem of extraction into posterior estimation and show its equivalence to energy minimization of a generalized active contour model. We discuss pertinent issues in shape training, energy minimization, line search strategies, minimax regularization and initialization by generalized Hough transform. Finally, we present experimental results and compare its performance to rigid template matching.
Persistent Identifierhttp://hdl.handle.net/10722/65517
ISSN
2015 Impact Factor: 6.077
2015 SCImago Journal Rankings: 7.653
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLai, Kok Fen_HK
dc.contributor.authorChin, Roland Ten_HK
dc.date.accessioned2010-08-31T07:15:01Z-
dc.date.available2010-08-31T07:15:01Z-
dc.date.issued1995en_HK
dc.identifier.citationIeee Transactions On Pattern Analysis And Machine Intelligence, 1995, v. 17 n. 11, p. 1084-1090en_HK
dc.identifier.issn0162-8828en_HK
dc.identifier.urihttp://hdl.handle.net/10722/65517-
dc.description.abstractThis paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local deformations, this yields prior distribution that exerts influence over a global model while allowing for deformations. We then cast the problem of extraction into posterior estimation and show its equivalence to energy minimization of a generalized active contour model. We discuss pertinent issues in shape training, energy minimization, line search strategies, minimax regularization and initialization by generalized Hough transform. Finally, we present experimental results and compare its performance to rigid template matching.en_HK
dc.languageengen_HK
dc.publisherI E E E. 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.subjectMarkov processesen_HK
dc.subjectMathematical modelsen_HK
dc.subjectMathematical transformationsen_HK
dc.subjectMatrix algebraen_HK
dc.titleDeformable contours: Modeling and extractionen_HK
dc.typeArticleen_HK
dc.identifier.emailChin, Roland T: rchin@hku.hken_HK
dc.identifier.authorityChin, Roland T=rp01300en_HK
dc.description.naturelink_to_subscribed_fulltexten_HK
dc.identifier.doi10.1109/34.473235en_HK
dc.identifier.scopuseid_2-s2.0-0029404006en_HK
dc.identifier.volume17en_HK
dc.identifier.issue11en_HK
dc.identifier.spage1084en_HK
dc.identifier.epage1090en_HK
dc.identifier.isiWOS:A1995TD85400007-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLai, Kok F=7402134987en_HK
dc.identifier.scopusauthoridChin, Roland T=7102445426en_HK

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