Computing Negentropy Based Signatures for Texture Recognition

dc.contributor.author	Lungu, Ana-Elena
dc.contributor.author	Colţuc, Daniela
dc.contributor.author	Frângu, Laurenţiu
dc.date.accessioned	2016-01-18T14:09:50Z
dc.date.available	2016-01-18T14:09:50Z
dc.date.issued	2007
dc.identifier.uri	http://10.11.10.50/xmlui/handle/123456789/3888
dc.description	The Annals of "Dunarea de Jos" University of Galati	en_US
dc.description.abstract	The proposed method aims to provide a new tool for texture recognition. For this purpose, a set of texture samples are decomposed by using the FastICA algorithm and characterized by a negentropy based signature. In order to do recognition, the texture signatures are compared by means of Minkowski distance. The recognition rates, computed for a set of 320 texture samples, show a medium recognition accuracy and the method may be further improved.	en_US
dc.language.iso	en	en_US
dc.subject	texture recognition	en_US
dc.subject	Independent Component Analysis	en_US
dc.subject	Minkowski distance	en_US
dc.title	Computing Negentropy Based Signatures for Texture Recognition	en_US
dc.type	Article	en_US