New recognition algorithm for various kinds of Euro banknotes
Jae-Kang Lee, Il-Hwan Kim · 2004
Counters for the various kinds of banknotes require high-speed distinctive point extraction and recognition. In this paper, we propose a new point extraction and recognition algorithm for banknotes. For distinctive point extraction we use a coordinate data extraction method from specific parts of a banknote representing the same color. To recognize banknotes, we trained 5 neural networks. One is for inserting direction and the others are for the face value. The algorithm is designed to minimize recognition time. The simulated results show the high recognition rate and low training period. The proposed method can be applied to high-speed banknote counting machines.