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.
|Title of host publication||IISA 2016 - 7th International Conference on Information, Intelligence, Systems and Applications|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|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
|Name||IISA 2016 - 7th International Conference on Information, Intelligence, Systems and Applications|
|Other||7th International Conference on Information, Intelligence, Systems and Applications, IISA 2016|
|Period||16/7/13 → 16/7/15|
Bibliographical notePublisher Copyright:
© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Artificial Intelligence
- Social Sciences (miscellaneous)