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dc.contributor.authorBusch, Andrewen_US
dc.description.abstractThe problem of determining the script and language of a document image has a number of important applications in the field of document analysis, for example as a precursor to OCR. Previous work has shown that visual texture is an effective method of performing script recognition, however such an approach is highly susceptible to changes in font. In this paper, a method of multi-font script recognition using a clustered discriminate function is proposed, allowing the training of a single model for each script class incorporating all fonts. Experimental evidence shows that such an approach can lead to significantly reduced error rates when classifying multi-font scripts.en_US
dc.publisherSchool of Microelectronic Engineering, Griffith Universityen_US
dc.publisher.placeNathan, QLD, Australiaen_US
dc.relation.ispartofconferencenameMicroelectronic Research Conference, 2005en_US
dc.relation.ispartofconferencetitleProceedings of Microelectronic Research Conference 2005en_US
dc.relation.ispartoflocationBrisbane, QLD, Australiaen_US
dc.titleMulti-font Script Identification Using Textureen_US
dc.typeConference outputen_US
dc.type.descriptionE2 - Conference Publications (Non HERDC Eligible)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.hasfulltextNo Full Text

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    Contains papers delivered by Griffith authors at national and international conferences.

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