Image classification and segmentation using multichannel fractal modeling

Kaloyeras Dimitrios, K; Kollias Stefanos, D

dc.contributor.author	Kaloyeras Dimitrios, K	en
dc.contributor.author	Kollias Stefanos, D	en
dc.date.accessioned	2014-03-01T02:48:07Z
dc.date.available	2014-03-01T02:48:07Z
dc.date.issued	1992	en
dc.identifier.issn	0277786X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33546
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0027003825&partnerID=40&md5=350babfdfd0d036403ac7cff0c6a6856	en
dc.subject.other	Classification (of information)	en
dc.subject.other	Color image processing	en
dc.subject.other	Fractals	en
dc.subject.other	Neural networks	en
dc.subject.other	Artificial neural networks	en
dc.subject.other	Fractal modeling	en
dc.subject.other	Image classification	en
dc.subject.other	Image segmentation	en
dc.subject.other	Multichannel fractal modeling	en
dc.subject.other	Segmentation	en
dc.subject.other	Image analysis	en
dc.title	Image classification and segmentation using multichannel fractal modeling	en
heal.type	conferenceItem	en
heal.publicationDate	1992	en
heal.abstract	Multichannel fractal modelling of the color images is proposed in this paper as an efficient tool for image classification and segmentation. An extension of the fractal dimension to appropriate matrix forms is used for this purpose, showing that it leads to more accurate representations of the original images. Various factors affecting these representations are investigated while artificial neural networks are used to classify the derived feature sets and segment the images.	en
heal.publisher	Publ by Int Soc for Optical Engineering, Bellingham, WA, United States	en
heal.journalName	Proceedings of SPIE - The International Society for Optical Engineering	en
dc.identifier.volume	1818	en
dc.identifier.issue	pt 3	en
dc.identifier.spage	950	en
dc.identifier.epage	957	en