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dc.contributor.advisorAli, Dr. Md. Haider
dc.contributor.advisorIslam, Md. Saiful
dc.contributor.authorAlimushwan, Munshi Md.
dc.contributor.authorMohaimin, Akiful
dc.contributor.authorIslam, Rifat
dc.contributor.authorChowdhury, Shahriar
dc.date.accessioned2017-01-19T05:29:18Z
dc.date.available2017-01-19T05:29:18Z
dc.date.copyright2016
dc.date.issued2016
dc.identifier.otherID 13301148
dc.identifier.otherID 12101139
dc.identifier.otherID 12101142
dc.identifier.otherID 11201016
dc.identifier.urihttp://hdl.handle.net/10361/7622
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 34-35).
dc.description.abstractFake notes area problem of almost every country. For country like Bangladesh it is becoming big hurdle. Fake Bangladeshi Currency of 1000 seems to have flooded the system and there is no proper way to deal with them for a common person. Therefore this has led to the increase of corruption in our country hindering country’s growth. Common man became a scapegoat for the fake currency circulation, let us suppose that a common man went to a bank to deposit money in bank but only to see that some of the notes are fake, in this case he has to take the blame. Because of the advances in printing, scanning technologies it is easily possible for a person to print fake notes with use of latest hardware tools. Detecting fake notes manually becomes time consuming and untidy process hence there is need of automation techniques with which currency recognition process can be efficiently done. The issue of efficiently distinguishing counterfeit banknotes from genuine ones via automatic machines has become more and more important. However, The main objective of this project is fake currency detection using MatLab. This process can be automated in a computer using the application software. The basic logic is developed using Image acquisition, gray scale conversion ,edge detection, image segmentation, feature extraction and comparison. The magnified image of the original currency is fed to the Matlab database. The features of the note to be tested are compared with the dataset formed from the original magnified image and finds out whether it is fake or original. The most important challenge is systematically and methodologically repeating the analysis process to reduce human error and time.en_US
dc.description.statementofresponsibilityMunshi Md. Alimushwan
dc.description.statementofresponsibilityAkiful Mohaimin
dc.description.statementofresponsibilityRifat Islam
dc.description.statementofresponsibilityShahriar Chowdhury
dc.format.extent35 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis 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 Acquisitionen_US
dc.subjectGray scale conversionen_US
dc.subjectEdge detectionen_US
dc.subjectImage segmentationen_US
dc.subjectFeature extractionen_US
dc.subjectMagnificationen_US
dc.subjectComparisonen_US
dc.titleFake currency detection using image processing methoden_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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