Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/146305
DC FieldValue
dc.titleDirectional feature detection and correspondence
dc.contributor.authorWang W.-H.
dc.contributor.authorHsiao F.-J.
dc.contributor.authorChen T.
dc.date.accessioned2018-08-21T05:09:33Z
dc.date.available2018-08-21T05:09:33Z
dc.date.issued2005
dc.identifier.citationWang W.-H., Hsiao F.-J., Chen T. (2005). Directional feature detection and correspondence. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3768 LNCS : 665-675. ScholarBank@NUS Repository.
dc.identifier.isbn3540300406
dc.identifier.isbn9783540300403
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/146305
dc.description.abstractA method is proposed to detect useful directional feature points other than corner points considering that the number of corner points may not be sufficient in a scene. This is achieved by directional analysis of properties of image points by virtue of the proposed gradient operators with different direction topologies. A matching criterion is also proposed to find the initial correspondence by using the feature vectors that are acquired from the results of directional analysis. For the purpose of improving the final correspondence, four constraints are employed in the system to seek and refine the correspondence.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentOFFICE OF THE PROVOST
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume3768 LNCS
dc.description.page665-675
dc.published.statepublished
Appears in Collections:Staff Publications

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