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.
Bibliographical noteFunding Information:
Funding: This research was supported by the Technology development Program (S2467392) funded by the Ministry of SMEs and Startups (MSS, Korea) and by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B4004231).
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
- Banknote recognition
- Counterfeit banknote detection
- Counterfeit detection system
- Explainable artificial intelligence
- Joint banknote recognition