IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Extraction for Bank Note Classification Using Wavelet Transform
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In order to improve the performance of the banknote classification, this paper presents a new feature extraction method based on quaternion wavelet transform (QWT). The QWT yields one shift invariant magnitude and three phases based on quaternion algebra. The generalized Gaussian density (GGD) is applied to capture the statistical characteristics of QWT coefficients. The neural network is used as classifier in the framework of banknote classification. Experimental results demonstrate its effectiveness and the proposed method obtains a higher recognition rate in the banknote classification.