ニューロ紙幣識別ボードの開発

抄録

Much research has been done to apply neural networks (NNs) to pattern recognition and the results have proved that recognition methods by NNs are effective. Up to this point, we have proposed a structure reduction method for NNs and have applied the method to paper currency recognition. In the method, we have adopted slab values which are generated by random masks. Still more, we have tried to optimize these random masks using genetic algorithm.
In this paper, in order to realize the neuro-paper currency recognition in the commercial products, we have developed a high-speed neuro-recognition board. This device can recognize paper currency firster than ten times compared with the conventional recognition machines. The device is constructed with digital signal processor (DSP) which is used in image processing widely. We denote its configuration and specification for paper currency recognition. Furthermore, we show its application to US dollars using this device on the prototype.