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http://dx.doi.org/10.7840/kics.2014.39B.7.459

An Implementation of Pattern Recognition Algorithm for Fast Paper Currency Counting  

Kim, Seon-Gu (Seetech Co.)
Kang, Byeong-Gwon (Department of Information & Communication Engineering, Soonchunhyang University)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.39B, no.7, 2014 , pp. 459-466 More about this Journal
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.
Keywords
Paper currency counting; Pattern recognition; Edge Histogram; NNR; Feature extraction;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 J. W. Lee and J. H. Lee, "Learning and recognition of banknotes by using neural network," J. Research Inst. Production Technol., Kyungsung University, vol. 2, pp. 67-76, Dec. 1995.
2 Y. C. Park, A study on learning fuzzy controller based on neural networks, Master Dissertation, Chungang University, 2000.
3 R. E. Neapolitan, Learning Bayesian Networks, Prentice-Hall, 2004.
4 F. Takeda and S. Omatu, "High speed paper currency recognition by neural networks," IEEE Trans. Neural Netw., vol. 6, no. 1, pp. 73-77, 1995.   DOI   ScienceOn
5 A. Frosini, M. Gori, and P. Priami, "A neural network-based model for paper currency recognition and verification," IEEE Trans. Neural Netw., vol. 7, no. 6, pp. 1482-1490, 1996.   DOI   ScienceOn
6 Martin T. Hagan, Howard B. Demuth, and Mark Beale, Neural Network Design, Boston, PWS Publishing Company, 1995.
7 S. H. Chae, Y. T. Seo, and S. B. Ban, "The study to distinguish kinds of banknote using color and size elements," in Proc. KIIT Summer Conf., pp. 234-237, 2009.
8 C. J. Lee, B. H. Son, and H. S. Hong, "Improvement of pattern recognition capacity of the fuzzy ART with the variable learning," J. KICS, vol. 38, no. 12, pp. 954-961, Dec. 2013.   과학기술학회마을   DOI
9 Y. S. Kang and C. S. Bae, "License plates detection using a Gaussian window," J. KICS, vol. 37, no. 9, pp. 780-785, Sept. 2012.
10 B. H. Song, M. S. Choi, J. W. Kwon, and S. R. Lee, "A design and implementation of digital vessel context diagnosis system based on context aware," J. KICS, vol. 35, no. 6, pp. 859-866, Jun. 2010.   과학기술학회마을
11 E. W. Cho, E. S. Ahn, J. K. Lee and I. H. Kim, "Feature abstraction and recognition algorithm for various kinds of banknote counting," J. Research Inst. Ind. Technol., Kangwon National University, vol. 22, no. A, pp. 101-105, 2002.
12 Y. H. Cho, S. H. Lee, and I. H. Seo, "Development of high-speed paper currency recognition system based on Bayesian rule," in Proc. KIEE Summer Conf., pp. 2474-2476, 2004.
13 F. Takeda and T. Nishikage, "Multiple kinds of paper currency recognition using neural network and application for euro currency," in Proc. IEEE-INNS-ENNS Int. Joint Conf. Neural Networks (IJCNN 2000), vol. 2, pp. 143-147, Como, Jul. 2000.
14 E.-H. Zhang, B. Jiang, J.-H. Duan, and Z.-Z. Bian, "Research on paper currency recognition by neural networks," in Proc. Int. Conf. Machine Learning and Cybernetics, vol. 4, pp. 2193-2197, Nov. 2003.
15 S. C. Kim, Banknote recognition and defect detection by edge histogram and mean-variance, Master Dissertation, Hanyang University, 2012
16 H. Hassanpour, A. Yaseri, and G. Ardeshiri, "Feature extraction for paper currency recognition," in Proc. Int. Symp. Signal Processing and Its Applications, ISSPA 2007, pp. 1-4, Sharjah, Feb. 2007.