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Published in:
2009 | OriginalPaper | Chapter
Classification of Fatigue Bill Based on Support Vector Machine by Using Acoustic Signal
Authors : Dongshik Kang, Masaki Higa, Nobuo Shoji, Masanobu Fujita, Ikugo Mitsui
Published in: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Publisher: Springer Berlin Heidelberg
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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 overworked and exhausted ones. An advanced technique is requested in order to classify the levels of fatigue as well as distinguish between the used and the new ones. Therefore, the purpose of this paper is to present the classification method of fatigue bills based on support vector machine(SVM) by using acoustic signals. The effectiveness of this approach is demonstrated by the bill identify experimentation based on the real acoustic signal.