Neural Network Recognition System Tuned by GA and Application of Foreign Paper Currencys

Neural Network Recognition System Tuned by GA and Application of Foreign Paper Currencys Fumiaki Takeda, Member (GLORY LTD.) We have proposed a paper currency recognition system by a neural network (NN) to develop new type of paper currency recognition machines. This system is constructed by some core techniques. One is the small scale neuro-recognition technique using masks. The other is the mask optimization technique using genetic algorithm (GA). In this mask optimizing technique, I have shown the effectiveness of the adopting GA. Up to now, it has been shown that the NN recognition and learning system are enough as a design and developing method in the market. However, in case of the mask optimizing system, it has not been shown yet. In this paper, I and my group implement this mask optimizing system using GA from EWS to personal computer. Then I show its pragmatic effectiveness and generalization using Italy, France, and Spain currencys. Furthermore, I show the relationship between the least masked area and mask optimized condition by the simulation result. Finally, I also refer running method of this mask optimizing system to aim at using as design and developing tools.