NDLI: Detection of fake banknotes with Artificial Neural Networks and Support Vector Machines

Content Provider	IEEE Xplore Digital Library
Author	Celik, E. Kondiloglu, A.
Copyright Year	2015
Description	Author affiliation: Bilgisayar Programciligi, Kirklareli Univ., Krklareli, Turkey (Celik, E.) \|\| Bilgisayar Muhendisligi, Turk Hava Kurumu Univ., Turkey (Kondiloglu, A.)
Abstract	The document and banknote counterfeiting remove us as a usurpation of the rights of individuals and institutions. By the advancement of technology special paper, the ink usage in the original banknote, placing watermarks, micro text are challenged to fraud that also does not prevent the counterfeiting of widespread. The counterfeit banknotes detection and minimizing damage is one of the important elements. In this, decided and expert systems can be improved to estimate the counterfeit banknotes to using dates of the moneys. The data of banknotes are sorted before to this point, after comparative results are discussed of the testing. In this study, it is classified by the classification algorithms to using digitized available data of real and counterfeit banknotes images. Artificial Neural Networks and Support Vector Machines are used in the classification. Correctly identified is detected to rate of 74.6% in the test results which is tested by Artificial Neural Networks, correctly identified is detected to rate of 93.8% in the results of tests which is tested by Support Vector Machines.
Starting Page	1317
Ending Page	1320
File Size	465623
Page Count	4
File Format	PDF
ISBN	9781467373869
DOI	10.1109/SIU.2015.7130082
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-16
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Conferences Artificial neural networks Mobile handsets Pattern recognition Security
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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