Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
special section
Fatigue level estimation of monetary bills based on frequency band acoustic signals with feature selection by supervised SOM
Masaru TeranishiSigeru OmatuToshihisa Kosaka
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JOURNALS FREE ACCESS

2010 Volume 1 Issue 1 Pages 69-78

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Abstract

Fatigued monetary bills adversely affect the daily operation of automated teller machines (ATMs). In order to make the classification of fatigued bills more efficient, the development of an automatic fatigued monetary bill classification method is desirable. We propose a new method by which to estimate the fatigue level of monetary bills from the feature-selected frequency band acoustic energy pattern of banking machines. By using a supervised self-organizing map (SOM), we effectively estimate the fatigue level using only the feature-selected frequency band acoustic energy pattern. Furthermore, the feature-selected frequency band acoustic energy pattern improves the estimation accuracy of the fatigue level of monetary bills by adding frequency domain information to the acoustic energy pattern. The experimental results with real monetary bill samples reveal the effectiveness of the proposed method.

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© 2010 The Institute of Electronics, Information and Communication Engineers
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