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dc.contributor.authorBozkurt, A.en_US
dc.contributor.authorDuygulu P.en_US
dc.contributor.authorCetin, A.E.en_US
dc.date.accessioned2016-02-08T10:54:04Z
dc.date.available2016-02-08T10:54:04Z
dc.date.issued2015en_US
dc.identifier.issn18631703
dc.identifier.urihttp://hdl.handle.net/11693/26035
dc.description.abstractRecognizing fonts has become an important task in document analysis, due to the increasing number of available digital documents in different fonts and emphases. A generic font recognition system independent of language, script and content is desirable for processing various types of documents. At the same time, categorizing calligraphy styles in handwritten manuscripts is important for paleographic analysis, but has not been studied sufficiently in the literature. We address the font recognition problem as analysis and categorization of textures. We extract features using complex wavelet transform and use support vector machines for classification. Extensive experimental evaluations on different datasets in four languages and comparisons with state-of-the-art studies show that our proposed method achieves higher recognition accuracy while being computationally simpler. Furthermore, on a new dataset generated from Ottoman manuscripts, we show that the proposed method can also be used for categorizing Ottoman calligraphy with high accuracy. © 2015, Springer-Verlag London.en_US
dc.language.isoEnglishen_US
dc.source.titleSignal, Image and Video Processingen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s11760-015-0795-zen_US
dc.subjectArabicen_US
dc.subjectChineseen_US
dc.subjectDual tree complex wavelet transformen_US
dc.subjectFont recognitionen_US
dc.subjectLatinen_US
dc.subjectOttoman calligraphyen_US
dc.subjectSVMen_US
dc.subjectComputational linguisticsen_US
dc.subjectPartial dischargesen_US
dc.subjectSupport vector machinesen_US
dc.subjectArabicen_US
dc.subjectChineseen_US
dc.subjectDual-tree complex wavelet transformen_US
dc.subjectFont recognitionen_US
dc.subjectLatinen_US
dc.subjectOttoman calligraphyen_US
dc.subjectSVMen_US
dc.subjectWavelet transformsen_US
dc.titleClassifying fonts and calligraphy styles using complex wavelet transformen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage225en_US
dc.citation.epage234en_US
dc.citation.volumeNumber9en_US
dc.identifier.doi10.1007/s11760-015-0795-zen_US
dc.publisherSpringer-Verlag London Ltden_US


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