A hybrid fake banknote detection model using OCR, face recognition and hough features
Cataloged from PDF version of thesis.
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| Teanga: | English |
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BRAC University
2018
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| Rochtain ar líne: | http://hdl.handle.net/10361/10846 |
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10361-10846 |
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10361-108462022-01-26T10:15:46Z A hybrid fake banknote detection model using OCR, face recognition and hough features Zarin, Adiba Tasnim, Ummay Jahan, Israt Uddin, Dr. Jia Department of Computer Science and Engineering, BRAC University Fake currency Counterfeit detection Digital image processing Human face recognition (Computer science) Banking--Security measures. Cataloged from PDF version of thesis. Includes bibliographical references (pages 26-28). This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. 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. Adiba Zarin Ummay Tasnim Israt Jahan B. Computer Science and Engineering 2018-11-14T05:33:30Z 2018-11-14T05:33:30Z 2018 8/13/2018 Thesis ID 13221030 ID 13321056 ID 13201018 http://hdl.handle.net/10361/10846 en 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. 28 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Fake currency Counterfeit detection Digital image processing Human face recognition (Computer science) Banking--Security measures. |
| spellingShingle |
Fake currency Counterfeit detection Digital image processing Human face recognition (Computer science) Banking--Security measures. Zarin, Adiba Tasnim, Ummay Jahan, Israt A hybrid fake banknote detection model using OCR, face recognition and hough features |
| description |
Cataloged from PDF version of thesis. |
| author2 |
Uddin, Dr. Jia |
| author_facet |
Uddin, Dr. Jia Zarin, Adiba Tasnim, Ummay Jahan, Israt |
| format |
Thesis |
| author |
Zarin, Adiba Tasnim, Ummay Jahan, Israt |
| author_sort |
Zarin, Adiba |
| title |
A hybrid fake banknote detection model using OCR, face recognition and hough features |
| title_short |
A hybrid fake banknote detection model using OCR, face recognition and hough features |
| title_full |
A hybrid fake banknote detection model using OCR, face recognition and hough features |
| title_fullStr |
A hybrid fake banknote detection model using OCR, face recognition and hough features |
| title_full_unstemmed |
A hybrid fake banknote detection model using OCR, face recognition and hough features |
| title_sort |
hybrid fake banknote detection model using ocr, face recognition and hough features |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/10846 |
| work_keys_str_mv |
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| _version_ |
1814308212672823296 |