Abstract
In Japan, ATMs or vending machines with a banknote handling device are widely used. The fatigued banknotes is the main reason of paper jam problems in those machines. Therefore a technique has demanded in order to distinguish fatigued banknotes more efficiently. In this paper, we propose a method to solve this problem by extracting the features of fatigued bills that is not depend greatly on the classifier. The method which extract the feature quantity of the frequency spectral difference from acoustic signals of banknotes. This feature quantity is possible to cope with time-series change of the acoustic signal by the fatigued degree of banknotes. And the discrimination experiments of fatigued banknotes were performed by Support Vector Machine(SVM) with the frequency spectral difference as input. The results showed that this feature quantity is effective to classify the fatigued banknotes.
