An Implementation of Pattern Recognition Algorithm for Fast Paper Currency Counting 


Vol. 39,  No. 7, pp. 459-466, Jul.  2014


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  Abstract

In this paper, we suggest an efficient image processing method for fast paper currency counting with pattern recognition. The patterns are consisted of feature data in each note object extracted from full reflection image of notes and a general contact image sensor(CIS) is used to aggregate the feature images. The proposed pattern recognition algorithm can endure image variation when the paper currency is scanned because it is not sensitive to changes of image resulting in successful note recognition. We tested 100 notes per denomination and currency of several countries including Korea, U.S., China, EU, Britain and Turkey. To ensure the reliability of the result, we tested a total of 10 times per each direction of notes. We can conclude that this algorithm will be applicable to commercial product because of its successful recognition rates. The 100% recognition rates are obtained in almost cases with exceptional case of 99.9% in Euro and 99.8% in Turkish Lira.

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  Cite this article

[IEEE Style]

S. Kim and B. Kang, "An Implementation of Pattern Recognition Algorithm for Fast Paper Currency Counting," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 7, pp. 459-466, 2014. DOI: .

[ACM Style]

Seon-Gu Kim and Byeong-Gwon Kang. 2014. An Implementation of Pattern Recognition Algorithm for Fast Paper Currency Counting. The Journal of Korean Institute of Communications and Information Sciences, 39, 7, (2014), 459-466. DOI: .

[KICS Style]

Seon-Gu Kim and Byeong-Gwon Kang, "An Implementation of Pattern Recognition Algorithm for Fast Paper Currency Counting," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 7, pp. 459-466, 7. 2014.