Abstract
An invariant feature extraction method is proposed for banknote classification. The movement of banknote is complex in the channel of financial instruments. The scale is various. The rotation and translation are also to occur. The method of feature extraction is insensitive to the variety of scale, rotation and translation. It decreases the data variety and improves the reliability of banknote classification. Furthermore, the computation complexity is low in order to meet to the requirement of real-time banknote image processing and classification. The invariant feature extraction method has performed very well when they are applied in banknote sorters.
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