Advances in texture analysis: Energy dominant component & multiple hypothesis testing

Kokkinos, I; Evangelopoulos, G; Maragos, P

dc.contributor.author	Kokkinos, I	en
dc.contributor.author	Evangelopoulos, G	en
dc.contributor.author	Maragos, P	en
dc.date.accessioned	2014-03-01T02:42:26Z
dc.date.available	2014-03-01T02:42:26Z
dc.date.issued	2004	en
dc.identifier.issn	15224880	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31009
dc.subject	Feature Extraction	en
dc.subject	Multiple Hypothesis Testing	en
dc.subject	Natural Images	en
dc.subject	Texture Analysis	en
dc.subject.other	Dominant component analysis (DCA)	en
dc.subject.other	Modulation signals	en
dc.subject.other	Natural images	en
dc.subject.other	Texture analysis	en
dc.subject.other	Boundary conditions	en
dc.subject.other	Classification (of information)	en
dc.subject.other	Fuzzy control	en
dc.subject.other	Image processing	en
dc.subject.other	Mathematical models	en
dc.subject.other	Problem solving	en
dc.subject.other	Textures	en
dc.title	Advances in texture analysis: Energy dominant component & multiple hypothesis testing	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2004.1421351	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2004.1421351	en
heal.publicationDate	2004	en
heal.abstract	Modelling textured images as AM-FM functions has been applied during the last years to texture analysis and segmentation tasks. In this paper we present some advances in two directions, namely the improvement of modulation feature extraction and texture vs. non texture discrimination. First we present a modified dominant AM-FM component analysis scheme based on non-linear energy operators. Subsequently we propose a novel approach to the discrimination between textured and non-textured image areas using multiband filter responses which is formulated as a statistical multiple hypothesis testing problem. The theoretical insights of this approach are supported by experimental validation using natural images. © 2004 IEEE.	en
heal.journalName	Proceedings - International Conference on Image Processing, ICIP	en
dc.identifier.doi	10.1109/ICIP.2004.1421351	en
dc.identifier.volume	3	en
dc.identifier.spage	1509	en
dc.identifier.epage	1512	en