Texture characterization representation description and classification based on gaussian markov random field model with bayesian approach

dc.contributor.guide	Seetharaman K
dc.coverage.spatial
dc.creator.researcher	Palanivel N
dc.date.accessioned	2017-05-24T05:14:08Z
dc.date.available	2017-05-24T05:14:08Z
dc.date.awarded	n.d
dc.date.completed	2015
dc.date.registered	n.d
dc.description.abstract	The texture of a surface is characterized by properties such as fine model based techniques are most appropriate newline
dc.description.note
dc.format.accompanyingmaterial	DVD
dc.format.dimensions
dc.format.extent	xiv, 112
dc.identifier.uri	http://hdl.handle.net/10603/151050
dc.language	English
dc.publisher.institution	Department of Computer Science and Engg.
dc.publisher.place	Tirunelveli
dc.publisher.university	Manonmaniam Sundaranar University
dc.relation	81
dc.rights	university
dc.source.university	University
dc.subject.keyword	development of useful algorithms
dc.subject.keyword	Fourier power spectrum
dc.subject.keyword	noncausal model given
dc.title	Texture characterization representation description and classification based on gaussian markov random field model with bayesian approach
dc.title.alternative
dc.type.degree	Ph.D.