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Finding point correspondence using local similarity and global constraint under insignificant scaling and roll

dc.citation.epage1342en_US
dc.citation.issue23en_US
dc.citation.spage1340en_US
dc.citation.volume42en_US
dc.citation.woscount1
dc.contributor.authorKao, J. -H.en_US
dc.contributor.authorChuang, J. -H.en_US
dc.contributor.authorHsieh, M. -L.en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.date.accessioned2014-12-08T15:15:23Z
dc.date.available2014-12-08T15:15:23Z
dc.date.issued2006-11-09en_US
dc.description.abstractEstablishing point correspondences is an important research topic in computer vision. Proposed is an algorithm using local similarity and global constraint to obtain point correspondence. The point correspondences are obtained by comparing their associated colour codes, which are computed by image gradients, and using spatial relationships among neighbouring feature points. The approach assumes insignificant scaling and roll, and is suitable for real-time applications.en_US
dc.identifier.doi10.1049/el:20062848en_US
dc.identifier.issn0013-5194en_US
dc.identifier.journalELECTRONICS LETTERSen_US
dc.identifier.urihttp://dx.doi.org/10.1049/el:20062848en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/11553
dc.identifier.wosnumberWOS:000242653800015
dc.language.isoen_USen_US
dc.titleFinding point correspondence using local similarity and global constraint under insignificant scaling and rollen_US
dc.typeArticleen_US

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