Image analysis for artistic style identification: A powerful tool for preserving cultural heritage

Doulamis, AD; Varvarigou, TA

dc.contributor.author	Doulamis, AD	en
dc.contributor.author	Varvarigou, TA	en
dc.date.accessioned	2014-03-01T02:53:41Z
dc.date.available	2014-03-01T02:53:41Z
dc.date.issued	2012	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36473
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-84856646825&partnerID=40&md5=e0ab7dc309904fd61ed248f28a44c3f0	en
dc.subject.other	Cultural heritages	en
dc.subject.other	Descriptors	en
dc.subject.other	Non-destruction	en
dc.subject.other	SIFT descriptors	en
dc.subject.other	Visual assessments	en
dc.subject.other	Motion Picture Experts Group standards	en
dc.subject.other	Network architecture	en
dc.subject.other	Nondestructive examination	en
dc.subject.other	Paint	en
dc.subject.other	Historic preservation	en
dc.title	Image analysis for artistic style identification: A powerful tool for preserving cultural heritage	en
heal.type	conferenceItem	en
heal.publicationDate	2012	en
heal.abstract	In this paper we propose a new adaptable neural network architecture able to identify the artistic style of paintings. This technique is a non-destruction method for preserving cultural heritage. Preserving visual paintings and restoring damages is one of the most salient actions in conserving work arts and antiquities. More specifically, the preservation procedure often follows not only current knowledge of the artist's common practices but they also include a visual assessment of the presence of the artist's ""handwriting"" in the brushwork. The features used are of two types; MPEG-7 visual descriptors and SIFT descriptors. We also propose scalable organization of the descriptors. © 2012 Taylor & Francis Group, London.	en
heal.journalName	Emerging Technologies in Non-Destructive Testing V - Proceedings of the 5th Conference on Emerging Technologies in NDT	en
dc.identifier.spage	71	en
dc.identifier.epage	76	en