DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Daniel | ko |
dc.contributor.author | Son, Seung-Woo | ko |
dc.contributor.author | Jeong, Ha-Woong | ko |
dc.date.accessioned | 2015-05-22T02:29:30Z | - |
dc.date.available | 2015-05-22T02:29:30Z | - |
dc.date.created | 2015-01-13 | - |
dc.date.created | 2015-01-13 | - |
dc.date.issued | 2014-12 | - |
dc.identifier.citation | SCIENTIFIC REPORTS, v.4 | - |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | http://hdl.handle.net/10203/198587 | - |
dc.description.abstract | Scientists 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.language | English | - |
dc.publisher | NATURE PUBLISHING GROUP | - |
dc.subject | STYLE | - |
dc.title | Large-Scale Quantitative Analysis of Painting Arts | - |
dc.type | Article | - |
dc.identifier.wosid | 000346287000001 | - |
dc.identifier.scopusid | 2-s2.0-84935002399 | - |
dc.type.rims | ART | - |
dc.citation.volume | 4 | - |
dc.citation.publicationname | SCIENTIFIC REPORTS | - |
dc.identifier.doi | 10.1038/srep07370 | - |
dc.contributor.localauthor | Jeong, Ha-Woong | - |
dc.contributor.nonIdAuthor | Son, Seung-Woo | - |
dc.description.isOpenAccess | Y | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordPlus | STYLE | - |
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