Abstract
With advancement of sensor technologies, it is now possible to manufacture cost-effective multispectral sensors for ATM (automatic teller machine). Using multispectral images, one can better cope with counterfeit banknote problems. In this paper, we propose a counterfeit banknote detection using multispectral images in visual and infrared spectrum. In the proposed method, we divided a banknote into a number of blocks and extracted features from the blocks. To reduce processing time for real-time applications, we applied block selection algorithms. Since ATMs have a limited computing power, we used linear and quadratic classifiers. Experimental results show promising results.
Original language | English |
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Title of host publication | IISA 2016 - 7th International Conference on Information, Intelligence, Systems and Applications |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781509034291 |
DOIs | |
Publication status | Published - 2016 Dec 14 |
Event | 7th International Conference on Information, Intelligence, Systems and Applications, IISA 2016 - Chalkidiki, Greece Duration: 2016 Jul 13 → 2016 Jul 15 |
Publication series
Name | IISA 2016 - 7th International Conference on Information, Intelligence, Systems and Applications |
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Other
Other | 7th International Conference on Information, Intelligence, Systems and Applications, IISA 2016 |
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Country/Territory | Greece |
City | Chalkidiki |
Period | 16/7/13 → 16/7/15 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Artificial Intelligence
- Social Sciences (miscellaneous)