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dc.contributor.advisorUddin, Jia
dc.contributor.authorZarin, Adiba
dc.contributor.authorTasnim, Ummay
dc.contributor.authorJahan, Israt
dc.date.accessioned2019-01-24T09:40:32Z
dc.date.available2019-01-24T09:40:32Z
dc.date.copyright2018
dc.date.issued2018-08
dc.identifier.otherID 13221030
dc.identifier.otherID 13321056
dc.identifier.otherID 13201018
dc.identifier.urihttp://hdl.handle.net/10361/11294
dc.descriptionThis thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 26-28).
dc.description.abstractCurrency duplication is now a common occurrence due to the advancement of printing and scanning technology. Many note detection systems are present in banks but they are very costly. In this paper, we are proposing an accurate and consistent technique for fake banknote recognition. We are developing an image processing algorithm which will extract different currency features and compare it with features of original note image. As an output, information about whether the note image is original or duplicate is given. Three main features of paper currencies has been implemented which are micro-printing, water-mark, and ultraviolet lines using OCR (Optical Character recognition), Face Recognition and Canny Edge & Hough transformation algorithm of Matlab. We apply these techniques in order to find an algorithm which will easily be applicable and will be efficient in terms of cost, reliability and accuracy. Along with 1000taka note has been tested for checking authenticity hence making our techniques more appropriate for users.en_US
dc.description.statementofresponsibilityAdiba Zarin
dc.description.statementofresponsibilityUmmay Tasnim
dc.description.statementofresponsibilityIsrat Jahan
dc.format.extent28 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsThis thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
dc.rightsBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectImage processingen_US
dc.subjectCounterfeit detectionen_US
dc.subjectFake currencyen_US
dc.subject.lcshFace perception.
dc.subject.lcshSCIENCE -- Cognitive Science.
dc.subject.lcshPSYCHOLOGY -- Cognitive Psychology.
dc.subject.lcshHuman information processing.
dc.subject.lcshPsycholinguistics.
dc.subject.lcshCognitive science.
dc.titleA hybrid fake banknote detection model using OCR, face recognition and hough featuresen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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