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Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/16528
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dc.contributor.authorQaiser, Naeemen_UK
dc.contributor.authorHussain, Mutawarraen_UK
dc.contributor.authorHussain, Amiren_UK
dc.contributor.authorQaiser, Nadeemen_UK
dc.date.accessioned2013-08-26T23:18:57Z-
dc.date.available2013-08-26T23:18:57Zen_UK
dc.date.issued2008-02en_UK
dc.identifier.urihttp://hdl.handle.net/1893/16528-
dc.description.abstractUse of a single technique for the extraction of diverse features in a texture image usually shows limited capabilities for texture description. Texture features extracted using different techniques can be merged in an attempt to enhance their texture description capability. This paper explores the fusion of optimized moment and Gabor energy texture features. The Fisher linear discriminant analysis is used to show that the discrimination effectiveness of the features increases as a result of the proposed fusion. Preliminary simulation results have been validated experimentally through the classification and segmentation of real texture images.en_UK
dc.language.isoenen_UK
dc.publisherInternational Journal of Computer Science and Network Securityen_UK
dc.relationQaiser N, Hussain M, Hussain A & Qaiser N (2008) Texture Recognition by Fusion of Optimized Moment Based and Gabor Energy Features. International Journal of Computer Science and Network Security, 8 (2), pp. 262-270. http://paper.ijcsns.org/07_book/200802/20080236.pdfen_UK
dc.rightsThe publisher has not yet responded to our queries therefore this work cannot be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.rights.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden_UK
dc.subjectMoment based texture featuresen_UK
dc.subjectGabor energy featuresen_UK
dc.subjectTexture classificationen_UK
dc.subjectFisher’s criterion Texture Segmentationen_UK
dc.subjectFusionen_UK
dc.titleTexture Recognition by Fusion of Optimized Moment Based and Gabor Energy Featuresen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2999-12-30en_UK
dc.rights.embargoreason[Texture Recognition by Fusion of Optimized Moment Based and Gabor Energy Features.pdf] The publisher has not yet responded to our queries. This work cannot be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.citation.jtitleInternational Journal of Computer Science and Network Securityen_UK
dc.citation.issn1738-7906en_UK
dc.citation.volume8en_UK
dc.citation.issue2en_UK
dc.citation.spage262en_UK
dc.citation.epage270en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.identifier.urlhttp://paper.ijcsns.org/07_book/200802/20080236.pdfen_UK
dc.author.emailamir.hussain@stir.ac.uken_UK
dc.contributor.affiliationPakistan Institute of Engineering and Applied Sciencesen_UK
dc.contributor.affiliationPakistan Institute of Engineering and Applied Sciencesen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationPakistan Institute of Engineering and Applied Sciencesen_UK
dc.identifier.wtid681917en_UK
dc.contributor.orcid0000-0002-8080-082Xen_UK
dcterms.dateAccepted2008-02-28en_UK
dc.date.filedepositdate2013-08-26en_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorQaiser, Naeem|en_UK
local.rioxx.authorHussain, Mutawarra|en_UK
local.rioxx.authorHussain, Amir|0000-0002-8080-082Xen_UK
local.rioxx.authorQaiser, Nadeem|en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2999-12-30en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||en_UK
local.rioxx.filenameTexture Recognition by Fusion of Optimized Moment Based and Gabor Energy Features.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1738-7906en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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