Enhanced document image Classification technique using Extreme learning machine classifier With fuzzy unsharp masking scheme

dc.contributor.guideSengotuvelan P
dc.coverage.spatialEnhanced document image Classification technique using Extreme learning machine classifier With fuzzy unsharp masking scheme
dc.creator.researcherBalamurugan E
dc.date.accessioned2017-02-13T08:59:32Z
dc.date.available2017-02-13T08:59:32Z
dc.date.awarded30/10/2015
dc.date.completed01/10/2015
dc.date.registeredn.d.
dc.description.abstractDocument Image Analysis for information extraction has very newlineprominent in recent years Document image is composed of a variety of newlinephysical entities or regions such as handwritten text machine printed newlinetexts blocks lines words figures tables and background Document newlineanalysis and recognition aims to automatic extraction of information newlinepresented in scanned documents The most widely known applications newlineof document analysis and recognition are processing of office newlinedocuments business letters forms engineering drawings and maps text newlinebooks technical manual musical notations and symbolic data Major newlineissues in the document analysis are removal of noise and artifacts that newlineare introduced during scanning phase segmentation feature extraction newlineand classification newline newline
dc.description.notep.166-178
dc.format.accompanyingmaterialNone
dc.format.dimensions23cm
dc.format.extentxvii, 179p.
dc.identifier.urihttp://hdl.handle.net/10603/134190
dc.languageEnglish
dc.publisher.institutionFaculty of Science and Humanities
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordfuzzy unsharp
dc.subject.keywordmachine classifier
dc.subject.keywordScience and humanities
dc.titleEnhanced document image Classification technique using Extreme learning machine classifier With fuzzy unsharp masking scheme
dc.title.alternative
dc.type.degreePh.D.

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