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

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Dades bibliogràfiques
Autors principals:	Zarin, Adiba, Tasnim, Ummay, Jahan, Israt
Altres autors:	Uddin, Jia
Format:	Thesis
Idioma:	English
Publicat:	BRAC University 2019
Matèries:	Image processing Counterfeit detection Fake currency Face perception. SCIENCE > Cognitive Science. PSYCHOLOGY > Cognitive Psychology. Human information processing. Psycholinguistics. Cognitive science.
Accés en línia:	http://hdl.handle.net/10361/11294

id	10361-11294
record_format	dspace
spelling	10361-112942022-01-26T10:10:32Z A hybrid fake banknote detection model using OCR, face recognition and hough features Zarin, Adiba Tasnim, Ummay Jahan, Israt Uddin, Jia Department of Computer Science and Engineering, BRAC University Image processing Counterfeit detection Fake currency Face perception. SCIENCE -- Cognitive Science. PSYCHOLOGY -- Cognitive Psychology. Human information processing. Psycholinguistics. Cognitive science. This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 26-28). 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 2019-01-24T09:40:32Z 2019-01-24T09:40:32Z 2018 2018-08 Thesis ID 13221030 ID 13321056 ID 13201018 http://hdl.handle.net/10361/11294 en This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. 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	Image processing Counterfeit detection Fake currency Face perception. SCIENCE -- Cognitive Science. PSYCHOLOGY -- Cognitive Psychology. Human information processing. Psycholinguistics. Cognitive science.
spellingShingle	Image processing Counterfeit detection Fake currency Face perception. SCIENCE -- Cognitive Science. PSYCHOLOGY -- Cognitive Psychology. Human information processing. Psycholinguistics. Cognitive science. Zarin, Adiba Tasnim, Ummay Jahan, Israt A hybrid fake banknote detection model using OCR, face recognition and hough features
description	This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
author2	Uddin, Jia
author_facet	Uddin, 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	2019
url	http://hdl.handle.net/10361/11294
work_keys_str_mv	AT zarinadiba ahybridfakebanknotedetectionmodelusingocrfacerecognitionandhoughfeatures AT tasnimummay ahybridfakebanknotedetectionmodelusingocrfacerecognitionandhoughfeatures AT jahanisrat ahybridfakebanknotedetectionmodelusingocrfacerecognitionandhoughfeatures AT zarinadiba hybridfakebanknotedetectionmodelusingocrfacerecognitionandhoughfeatures AT tasnimummay hybridfakebanknotedetectionmodelusingocrfacerecognitionandhoughfeatures AT jahanisrat hybridfakebanknotedetectionmodelusingocrfacerecognitionandhoughfeatures
_version_	1814307783742324736

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

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