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A hybrid fake banknote detection model using OCR, face recognition and hough features

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dc.contributor.advisor Uddin, Jia
dc.contributor.author Zarin, Adiba
dc.contributor.author Tasnim, Ummay
dc.contributor.author Jahan, Israt
dc.date.accessioned 2019-01-24T09:40:32Z
dc.date.available 2019-01-24T09:40:32Z
dc.date.copyright 2018
dc.date.issued 2018-08
dc.identifier.other ID 13221030
dc.identifier.other ID 13321056
dc.identifier.other ID 13201018
dc.identifier.uri http://hdl.handle.net/10361/11294
dc.description This 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.description Cataloged from PDF version of thesis.
dc.description Includes bibliographical references (pages 26-28).
dc.description.abstract Currency 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.statementofresponsibility Adiba Zarin
dc.description.statementofresponsibility Ummay Tasnim
dc.description.statementofresponsibility Israt Jahan
dc.format.extent 28 pages
dc.language.iso en en_US
dc.publisher BRAC University en_US
dc.rights This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
dc.rights BRAC 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.subject Image processing en_US
dc.subject Counterfeit detection en_US
dc.subject Fake currency en_US
dc.subject.lcsh Face perception.
dc.subject.lcsh SCIENCE -- Cognitive Science.
dc.subject.lcsh PSYCHOLOGY -- Cognitive Psychology.
dc.subject.lcsh Human information processing.
dc.subject.lcsh Psycholinguistics.
dc.subject.lcsh Cognitive science.
dc.title A hybrid fake banknote detection model using OCR, face recognition and hough features en_US
dc.type Thesis en_US
dc.contributor.department Department of Computer Science and Engineering, BRAC University
dc.description.degree B. Computer Science and Engineering


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