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Sensors 2016, 16(3), 328; doi:10.3390/s16030328

Efficient Banknote Recognition Based on Selection of Discriminative Regions with One-Dimensional Visible-Light Line Sensor

1
Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea
2
Kisan Electronics, Sungsoo 2-ga 3-dong, Sungdong-gu, Seoul 133-831, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 11 January 2016 / Revised: 22 February 2016 / Accepted: 22 February 2016 / Published: 4 March 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [16134 KB, uploaded 4 March 2016]   |  

Abstract

Banknote papers are automatically recognized and classified in various machines, such as vending machines, automatic teller machines (ATM), and banknote-counting machines. Previous studies on automatic classification of banknotes have been based on the optical characteristics of banknote papers. On each banknote image, there are regions more distinguishable than others in terms of banknote types, sides, and directions. However, there has been little previous research on banknote recognition that has addressed the selection of distinguishable areas. To overcome this problem, we propose a method for recognizing banknotes by selecting more discriminative regions based on similarity mapping, using images captured by a one-dimensional visible light line sensor. Experimental results with various types of banknote databases show that our proposed method outperforms previous methods. View Full-Text
Keywords: banknote recognition; selection of distinguishable areas; one-dimensional visible-light line sensor; various types of banknote databases banknote recognition; selection of distinguishable areas; one-dimensional visible-light line sensor; various types of banknote databases
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pham, T.D.; Park, Y.H.; Kwon, S.Y.; Park, K.R.; Jeong, D.S.; Yoon, S. Efficient Banknote Recognition Based on Selection of Discriminative Regions with One-Dimensional Visible-Light Line Sensor. Sensors 2016, 16, 328.

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