File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Matching patterns of line segments by eigenvector decomposition

TitleMatching patterns of line segments by eigenvector decomposition
Authors
Chan, BHBHung, YS
KeywordsComputer vision
Eigenvalues and eigenfunctions
Equations
Image edge detection
Image segmentation
Matrix decomposition
Pattern matching
Testing
World Wide Web
Issue Date2002
PublisherIEEE.
Citation
The 5th IEEE Southwest Symposium on Image Analysis and Interpretation Proceedings, Sante Fe, NM., 7-9 April 2002, p. 286-289 How to Cite?
DOI: http://dx.doi.org/10.1109/IAI.2002.999934
AbstractThis paper presents an algorithm for matching line segments in two images which are related by an affine transformation. Images are represented as patterns Of line segments. Areas defined between line segments are used to describe a line pattern in the form of a proximity matrix. Matches are determined by comparing the feature vectors obtained from eigenvalue decomposition of the proximity matrices. Reliable matches of line segments are obtained in both synthetic and real images.
Persistent Identifierhttp://hdl.handle.net/10722/46292

 

DC FieldValueLanguage
dc.contributor.authorChan, BHBen_HK
dc.contributor.authorHung, YSen_HK
dc.date.accessioned2007-10-30T06:46:38Z-
dc.date.available2007-10-30T06:46:38Z-
dc.date.issued2002en_HK
dc.identifier.citationThe 5th IEEE Southwest Symposium on Image Analysis and Interpretation Proceedings, Sante Fe, NM., 7-9 April 2002, p. 286-289en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46292-
dc.description.abstractThis paper presents an algorithm for matching line segments in two images which are related by an affine transformation. Images are represented as patterns Of line segments. Areas defined between line segments are used to describe a line pattern in the form of a proximity matrix. Matches are determined by comparing the feature vectors obtained from eigenvalue decomposition of the proximity matrices. Reliable matches of line segments are obtained in both synthetic and real images.en_HK
dc.format.extent482377 bytes-
dc.format.extent1795 bytes-
dc.format.extent3891 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Southwest Symposium on Image Analysis and Interpretation Proceedings-
dc.rights©2002 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.subjectComputer vision-
dc.subjectEigenvalues and eigenfunctions-
dc.subjectEquations-
dc.subjectImage edge detection-
dc.subjectImage segmentation-
dc.subjectMatrix decomposition-
dc.subjectPattern matching-
dc.subjectTesting-
dc.subjectWorld Wide Web-
dc.titleMatching patterns of line segments by eigenvector decompositionen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IAI.2002.999934en_HK
dc.identifier.scopuseid_2-s2.0-52049114853-
dc.identifier.hkuros70032-

Export via OAI-PMH Interface in XML Formats

OR

Export to Other Non-XML Formats