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The new area subdivision methods for producing shapes of colored paper mosaic

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dc.contributor.authorSeo, Sang Hyun-
dc.contributor.authorKang, Dae Wook-
dc.contributor.authorPark, Young Sub-
dc.contributor.authorYoon, Kyung Hyun-
dc.date.accessioned2021-11-30T07:40:41Z-
dc.date.available2021-11-30T07:40:41Z-
dc.date.issued2002-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/52049-
dc.description.abstractThis paper proposes a colored paper mosaic rendering technique based on image segmentation that can automatically generate a torn and tagged colored paper mosaic effect. The previous method[12] did not produce satisfactory results due to the ineffectiveness of having to use pieces of the same size. The proposed two methods for determination of paper shape and location that are based on segmentation can subdivide an image area by considering characteristics of image. The first method is to generate a Voronoi polygon after subdividing the segmented image again using a quad tree. And the second method is to apply the Voronoi diagram on each segmentation layer. Through these methods, the characteristic of the image is expressed in more detail than the previous colored paper mosaic rendering method.-
dc.format.extent10-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleThe new area subdivision methods for producing shapes of colored paper mosaic-
dc.typeArticle-
dc.identifier.doi10.1007/3-540-46080-2_4-
dc.identifier.bibliographicCitationCOMPUTATIONAL SCIENCE-ICCS 2002, PT II, PROCEEDINGS, v.2330, no.PART 2, pp 32 - 41-
dc.description.isOpenAccessN-
dc.identifier.wosid000181351000004-
dc.identifier.scopusid2-s2.0-84886830442-
dc.citation.endPage41-
dc.citation.numberPART 2-
dc.citation.startPage32-
dc.citation.titleCOMPUTATIONAL SCIENCE-ICCS 2002, PT II, PROCEEDINGS-
dc.citation.volume2330-
dc.type.docTypeArticle; Proceedings Paper-
dc.publisher.location독일-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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