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dc.contributor.authorMelit Devassy, Binu
dc.contributor.authorGeorge, Sony
dc.contributor.authorHardeberg, Jon Yngve
dc.date.accessioned2020-05-18T09:52:50Z
dc.date.available2020-05-18T09:52:50Z
dc.date.created2020-03-24T13:52:12Z
dc.date.issued2019
dc.identifier.urihttps://hdl.handle.net/11250/2654755
dc.description.abstractInk classification is an active topic in historic and forensic document analysis. In this work, we compared the ink classification capabilities of five commonly used and wellproven similarity measures for classification of hyperspectral imaging (HSI). They are Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), Euclidean Distance (ED), Spectral Information Divergence (SID) and Binary Encoding (BE). These techniques were well explored in different fields of HSI; however, they are not investigated in the field of ink classification. This study reveals the ink classification capabilities of these similarity measures. A combination of different types and colors of inks from different manufactures were used to create sample text. The SAM obtained higher accuracy compared to other methods and also identified that, inks that have nearly similar spectral signatures, cause a decline in accuracies due to misclassification between similar classes.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.titleComparison of Ink Classification Capabilities of Classic Hyperspectral Similarity Featuresen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.source.journalProceedings of 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW)en_US
dc.identifier.doi10.1109/ICDARW.2019.70137
dc.identifier.cristin1803253
dc.description.localcode© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.fulltextpostprint


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