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A Comparative Study of Rotation Angle Estimation Methods Based on Complex Moments

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dc.contributor.authorLee, Jong-Min-
dc.contributor.authorKim, Whoi-Yul-
dc.date.accessioned2024-12-20T06:24:04Z-
dc.date.available2024-12-20T06:24:04Z-
dc.date.issued2012-05-
dc.identifier.issn0916-8532-
dc.identifier.issn1745-1361-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/202615-
dc.description.abstractDetermining the rotation angle between two images is essential when comparing images that may include rotational variation. While there are three representative methods that utilize the phases of Zernike moments (ZMs) to estimate rotation angles, very little work has been done to compare the performances of these methods. In this paper, we compare the performances of these three methods and propose a new, angular radial transform (ART)-based method. Our method extends Revaud et al.'s method [1] and uses the phase of angular radial transform coefficients instead of ZMs. We show that our proposed method outperforms the ZM-based method using the MPEG-7 shape dataset when computation times are compared or in terms of the root mean square error vs. coverage.-
dc.format.extent9-
dc.language영어-
dc.language.isoENG-
dc.publisherOxford University Press-
dc.titleA Comparative Study of Rotation Angle Estimation Methods Based on Complex Moments-
dc.typeArticle-
dc.publisher.location일본-
dc.identifier.doi10.1587/transinf.E95.D.1485-
dc.identifier.scopusid2-s2.0-84860613852-
dc.identifier.wosid000304573100033-
dc.identifier.bibliographicCitationIEICE Transactions on Information and Systems, v.E95D, no.5, pp 1485 - 1493-
dc.citation.titleIEICE Transactions on Information and Systems-
dc.citation.volumeE95D-
dc.citation.number5-
dc.citation.startPage1485-
dc.citation.endPage1493-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.subject.keywordPlusIMAGE-ANALYSIS-
dc.subject.keywordPlusOBJECT RECOGNITION-
dc.subject.keywordAuthorrotation angle-
dc.subject.keywordAuthorphase-
dc.subject.keywordAuthorZernike moment-
dc.identifier.urlhttps://www.jstage.jst.go.jp/article/transinf/E95.D/5/E95.D_5_1485/_article-
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서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles

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