Neuro-classification of bill fatigue levels based on acoustic wavelet components

Abstract

This paper proposes a new method to classify bills(paper moneys) into different fatigue levels due to the extent of their damage. While a bill passing through a banking machine, a characteristic acoustic signal is emitted from the bill. To classify the acoustic signal into three bill fatigue levels, we calculate the acoustic wavelet power pattern as the input to a competitive neural networkwith the Learning Vector Quantization(LVQ) algorithm. The experimental results show that the proposed method can obtain better classification performance than the best of conventional acoustic signal based classification methods. It is, consequently, the LVQ algorithm demonstrates a good classification. © Springer-Verlag Berlin Heidelberg 2002.