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

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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 http://hdl.handle.net/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


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