Joint banknote recognition and counterfeit detection using explainable artificial intelligence

Miseon Han, Jeongtae Kim

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We investigated machine learning-based joint banknote recognition and counterfeit detection method. Unlike existing methods, since the proposed method simultaneously recognize banknote type and detect counterfeit detection, it is significantly faster than existing serial banknote recognition and counterfeit detection methods. Furthermore, we propose an explainable artificial intelligence method for visualizing regions that contributed to the recognition and detection. Using the visualization, it is possible to understand the behavior of the trained machine learning system. In experiments using the United State Dollar and the European Union Euro banknotes, the proposed method shows significant improvement in computation time from conventional serial method.

Original languageEnglish
Article number3607
JournalSensors (Switzerland)
Volume19
Issue number16
DOIs
StatePublished - 2 Aug 2019

Keywords

  • Banknote recognition
  • Counterfeit banknote detection
  • Counterfeit detection system
  • Explainable artificial intelligence
  • Joint banknote recognition

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