File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Bidirectional deformable matching with application to handwritten character extraction

TitleBidirectional deformable matching with application to handwritten character extraction
Authors
KeywordsBayesian inference
Bidirectional matching
Deformable models
Hausdorff matching
Model-based segmentation
Issue Date2002
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, 2002, v. 24 n. 8, p. 1133-1139 How to Cite?
AbstractTo achieve integrated segmentation and recognition in complex scenes, the model-based approach has widely been accepted as a promising paradigm. However, the performance is still far from satisfactory when the target object is highly deformed and the level of outlier contamination is high. In this paper, we first describe two Bayesian frameworks, one for classifying input patterns and another for detecting target patterns in complex scenes using deformable models. Then, we show that the two frameworks are similar to the forward-reverse setting of Hausdorff matching and that their matching and discriminating properties are complementary to each other. By properly combining the two frameworks, we propose a new matching scheme called bidirectional matching. This combined approach inherits the advantages of the two Bayesian frameworks. In particular, we have obtained encouraging empirical results on shape-based pattern extraction, using a subset of the CEDAR handwriting database containing handwritten words of highly varying shape.
Persistent Identifierhttp://hdl.handle.net/10722/65515
ISSN
2015 Impact Factor: 6.077
2015 SCImago Journal Rankings: 7.653
References

 

DC FieldValueLanguage
dc.contributor.authorCheung, KWen_HK
dc.contributor.authorYeung, DYen_HK
dc.contributor.authorChin, RTen_HK
dc.date.accessioned2010-08-31T07:15:00Z-
dc.date.available2010-08-31T07:15:00Z-
dc.date.issued2002en_HK
dc.identifier.citationIeee Transactions On Pattern Analysis And Machine Intelligence, 2002, v. 24 n. 8, p. 1133-1139en_HK
dc.identifier.issn0162-8828en_HK
dc.identifier.urihttp://hdl.handle.net/10722/65515-
dc.description.abstractTo achieve integrated segmentation and recognition in complex scenes, the model-based approach has widely been accepted as a promising paradigm. However, the performance is still far from satisfactory when the target object is highly deformed and the level of outlier contamination is high. In this paper, we first describe two Bayesian frameworks, one for classifying input patterns and another for detecting target patterns in complex scenes using deformable models. Then, we show that the two frameworks are similar to the forward-reverse setting of Hausdorff matching and that their matching and discriminating properties are complementary to each other. By properly combining the two frameworks, we propose a new matching scheme called bidirectional matching. This combined approach inherits the advantages of the two Bayesian frameworks. In particular, we have obtained encouraging empirical results on shape-based pattern extraction, using a subset of the CEDAR handwriting database containing handwritten words of highly varying shape.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.subjectBayesian inferenceen_HK
dc.subjectBidirectional matchingen_HK
dc.subjectDeformable modelsen_HK
dc.subjectHausdorff matchingen_HK
dc.subjectModel-based segmentationen_HK
dc.titleBidirectional deformable matching with application to handwritten character extractionen_HK
dc.typeArticleen_HK
dc.identifier.emailChin, RT: rchin@hku.hken_HK
dc.identifier.authorityChin, RT=rp01300en_HK
dc.description.naturelink_to_subscribed_fulltexten_HK
dc.identifier.doi10.1109/TPAMI.2002.1024135en_HK
dc.identifier.scopuseid_2-s2.0-0036685066en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036685066&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume24en_HK
dc.identifier.issue8en_HK
dc.identifier.spage1133en_HK
dc.identifier.epage1139en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridCheung, KW=55413672000en_HK
dc.identifier.scopusauthoridYeung, DY=7103391392en_HK
dc.identifier.scopusauthoridChin, RT=7102445426en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats