Fatigue level estimation of monetary bills based on frequency band acoustic signals with feature selection by supervised SOM

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概要

• 論文の詳細を見る

• 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.

著者

• Omatu Sigeru

  Department Of Computer And System Sciences College Of Engineering Osaka Prefecture University

• KOSAKA Toshihisa

  Glory Ltd.

• Omatu Sigeru

  Department of Electronics, Information and Communication Engineering, Osaka Institute of Technology

• Teranishi Masaru

  Department of Information Systems and Management, Hiroshima Institute of Technology

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