Show simple item record

dc.contributor.authorYan, W-Q
dc.contributor.authorChambers, J
dc.contributor.authorGarhwal, A
dc.date.accessioned2013-12-31T04:00:48Z
dc.date.accessioned2014-01-24T07:29:38Z
dc.date.available2013-12-31T04:00:48Z
dc.date.available2014-01-24T07:29:38Z
dc.date.copyright2013-12-31
dc.date.issued2013-12-31
dc.identifier.citationMultimedia Tools and Applications, pp.1 - 13 (13), doi: 10.1007/s11042-013-1833-x
dc.identifier.urihttp://hdl.handle.net/10292/6568
dc.description.abstractCurrency identification is the application of systematic methods to determine authenticity of questioned currency. However, identification analysis is a difficult task requiring specially trained examiners, the most important challenge is automating the analysis process reducing human labor and time. In this study, an empirical approach for automated currency identification is formulated and a prototype is developed. A two parts feature vector is defined comprised of color features and texture features. Finally the banknote in question is classified by a Feedforward Neural Network (FNN) and a measurement of the similarity between existing samples and suspect banknote is output.
dc.languageEnglish
dc.publisherSpringer
dc.relation.replaceshttp://hdl.handle.net/10292/6352
dc.relation.replaces10292/6352
dc.relation.urihttp://dx.doi.org/10.1007/s11042-013-1833-x
dc.rightsAn author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).
dc.subjectCurrency identification
dc.subjectNeural network
dc.subjectEmpirical approach
dc.titleAn empirical approach for currency identification
dc.typeJournal Article
dc.rights.accessrightsOpenAccess
dc.identifier.doi10.1007/s11042-013-1833-x
aut.relation.endpage13
aut.relation.pages13
aut.relation.startpage1
pubs.elements-id159778


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record