The bills in circulation generate a large amount of fatigue bills every year, causing various types of problems, such as the paper jam in automatic tellers due to overwork and exhaustion. A highly advanced bill classification technique, which distinguishes whether a bill is a reusable bill specifying the level of fatigue, is greatly required in order to comb out these problematic bills. Therefore, a purpose of this paper is to suggest a classification method of fatigue bills based on K-means with bill image data. The effectiveness of this approach is verified by the bill discriminant experimentation. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Kang, D., Miyaguni, S., Miyagi, H., Mitsui, I., Ozawa, K., Fujita, M., & Shoji, N. (2010). Classification of fatigue bills based on K-means by using creases feature. In Advances in Intelligent and Soft Computing (Vol. 79, pp. 27–33). https://doi.org/10.1007/978-3-642-14883-5_4
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