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Computer Optics, 2017, Volume 41, Issue 2, Pages 237–244
DOI: https://doi.org/10.18287/2412-6179-2017-41-2-237-244
(Mi co380)
 

This article is cited in 1 scientific paper (total in 1 paper)

IMAGE PROCESSING, PATTERN RECOGNITION

Ñounterfeit bill detection by image analysis for smartphones

Yu. B. Blokhinov, A. V. Bondarenko, V. A. Gorbachev, S. Yu. Zheltov, Yu. O. Rakutin

State Research Institute of Aviation Systems, Moscow, Russia
References:
Abstract: A method for counterfeit bill detection based on a digital image for mass-production smartphones is developed. The method under consideration does not require new protective elements to be designed and introduced into the print and is based on the use of digital image analysis and recognition methods, allowing one to carry out an automatic search and verification of known protective elements of the print. The peculiarity of the proposed approach is associated with constructing a feature vector for each type of samples and their subsequent classification using machine learning based on a training sample. The method is realized as a program application for smartphones, performing the automatic detection of an object in the frame, shooting the cameracaptured object, rejection of unsuitable images, determination of a face-value and type of the banknote, and finally, verification of the authenticity.
Keywords: digital image processing, image analysis, pattern recognition, banknote, counterfeit, smartphone, identification, authentication, feature vector, learning classification.
Received: 12.12.2016
Accepted: 08.02.2017
Document Type: Article
Language: Russian
Citation: Yu. B. Blokhinov, A. V. Bondarenko, V. A. Gorbachev, S. Yu. Zheltov, Yu. O. Rakutin, “Ñounterfeit bill detection by image analysis for smartphones”, Computer Optics, 41:2 (2017), 237–244
Citation in format AMSBIB
\Bibitem{BloBonGor17}
\by Yu.~B.~Blokhinov, A.~V.~Bondarenko, V.~A.~Gorbachev, S.~Yu.~Zheltov, Yu.~O.~Rakutin
\paper Ñounterfeit bill detection by image analysis for smartphones
\jour Computer Optics
\yr 2017
\vol 41
\issue 2
\pages 237--244
\mathnet{http://mi.mathnet.ru/co380}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-2-237-244}
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  • https://www.mathnet.ru/eng/co380
  • https://www.mathnet.ru/eng/co/v41/i2/p237
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    Full-text PDF :76
    References:39
     
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