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Conference Paper: PCTV: A biologically- and psychologically-inspired edge and line detection

TitlePCTV: A biologically- and psychologically-inspired edge and line detection
Authors
KeywordsEdge detection
Line detection
Phase congruency
Primary visual cortex (V1)
Tensor voting
Issue Date2010
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000349
Citation
The 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, 26-29 September 2010. In Proceedings of the 17th IEEE ICIP, 2010, p. 1621-1624 How to Cite?
AbstractA novel method for detecting edges and lines simultaneously and automatically is proposed. This method, based on phase congruency and tensor voting (hence PCTV), makes use of the properties of how edges and lines are built from the Fourier decomposition of an image, and how the primary visual cortex responds to them, instead of making assumptions on the intensity profiles of the regions near a feature. Experiments showed that the detection results were more consistent to the "ground truth" manually drawn by humans. For detecting edges, this method is superior to three commonly used detectors in that it reduces the production of false detections. © 2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/135972
ISSN
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorKang, Xen_HK
dc.contributor.authorCheung, PYSen_HK
dc.contributor.authorYau, WPen_HK
dc.contributor.authorHu, Yen_HK
dc.date.accessioned2011-07-27T02:00:45Z-
dc.date.available2011-07-27T02:00:45Z-
dc.date.issued2010en_HK
dc.identifier.citationThe 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, 26-29 September 2010. In Proceedings of the 17th IEEE ICIP, 2010, p. 1621-1624en_HK
dc.identifier.issn1522-4880en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135972-
dc.description.abstractA novel method for detecting edges and lines simultaneously and automatically is proposed. This method, based on phase congruency and tensor voting (hence PCTV), makes use of the properties of how edges and lines are built from the Fourier decomposition of an image, and how the primary visual cortex responds to them, instead of making assumptions on the intensity profiles of the regions near a feature. Experiments showed that the detection results were more consistent to the "ground truth" manually drawn by humans. For detecting edges, this method is superior to three commonly used detectors in that it reduces the production of false detections. © 2010 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000349en_HK
dc.relation.ispartofProceedings of the International Conference on Image Processing, ICIP 2010en_HK
dc.rightsInternational Conference on Image Processing Proceedings. Copyright © IEEE.-
dc.rights©2010 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.subjectEdge detectionen_HK
dc.subjectLine detectionen_HK
dc.subjectPhase congruencyen_HK
dc.subjectPrimary visual cortex (V1)en_HK
dc.subjectTensor votingen_HK
dc.titlePCTV: A biologically- and psychologically-inspired edge and line detectionen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailCheung, PYS:paul.cheung@hku.hken_HK
dc.identifier.emailYau, WP:peterwpy@hkucc.hku.hken_HK
dc.identifier.authorityCheung, PYS=rp00077en_HK
dc.identifier.authorityYau, WP=rp00500en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICIP.2010.5648890en_HK
dc.identifier.scopuseid_2-s2.0-78651071602en_HK
dc.identifier.hkuros188653en_US
dc.identifier.hkuros208271-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78651071602&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1621en_HK
dc.identifier.epage1624en_HK
dc.identifier.isiWOS:000287728001178-
dc.publisher.placeUnited Statesen_HK
dc.description.otherThe 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, 26-29 September 2010. In Proceedings of the 17th IEEE ICIP, 2010, p. 1621-1624-
dc.identifier.scopusauthoridKang, X=36844160400en_HK
dc.identifier.scopusauthoridCheung, PYS=7202595335en_HK
dc.identifier.scopusauthoridYau, WP=7005822441en_HK
dc.identifier.scopusauthoridHu, Y=36843933600en_HK

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