Large-Scale Quantitative Analysis of Painting Arts

Cited 47 time in webofscience Cited 45 time in scopus
  • Hit : 815
  • Download : 466
DC FieldValueLanguage
dc.contributor.authorKim, Danielko
dc.contributor.authorSon, Seung-Wooko
dc.contributor.authorJeong, Ha-Woongko
dc.date.accessioned2015-05-22T02:29:30Z-
dc.date.available2015-05-22T02:29:30Z-
dc.date.created2015-01-13-
dc.date.created2015-01-13-
dc.date.issued2014-12-
dc.identifier.citationSCIENTIFIC REPORTS, v.4-
dc.identifier.issn2045-2322-
dc.identifier.urihttp://hdl.handle.net/10203/198587-
dc.description.abstractScientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images - the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances.-
dc.languageEnglish-
dc.publisherNATURE PUBLISHING GROUP-
dc.subjectSTYLE-
dc.titleLarge-Scale Quantitative Analysis of Painting Arts-
dc.typeArticle-
dc.identifier.wosid000346287000001-
dc.identifier.scopusid2-s2.0-84935002399-
dc.type.rimsART-
dc.citation.volume4-
dc.citation.publicationnameSCIENTIFIC REPORTS-
dc.identifier.doi10.1038/srep07370-
dc.contributor.localauthorJeong, Ha-Woong-
dc.contributor.nonIdAuthorSon, Seung-Woo-
dc.description.isOpenAccessY-
dc.type.journalArticleArticle-
dc.subject.keywordPlusSTYLE-
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 47 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0