Research and Implementation for Intelligent Currency Recognition Method with Applied Neural Networks

到目前为止，作者的研究主要集中在神经网络在纸币识别中的应用。特别是，我们通过将神经识别系统应用于各种银行机器，明确了神经识别系统在工业应用中的有效性，尽管有不聚焦的传感数据和各种噪声数据。最近，将出现另一种对纸币识别的要求。也就是说，根据欧元钞票的外观，需要在银行机器上同时识别更多的钞票。为了解决这一问题，我们提出了一种由多个神经网络构造模板的神经模板匹配方法。通过对各种外国纸币和欧元假人的实验，证明了该方法的有效性。此外，我们还将该方法扩展到利用生物参数信息（如掌纹、指纹、人脸图像等）的人体安全领域。第一阶段，研究神经模板匹配识别算法。在此基础上，通过对外币纸币和欧元纸币的仿真，验证了该方法的有效性。同时，对DSP板进行了设计，并在该DSP板上实现了本文提出的算法。第二阶段，将该识别算法和DSP板应用于落米笔压检测系统的个体识别。然后在实时系统中验证了该算法的有效性和实用性。

Up to now, Authors research have been focused on applications of neural networks (NNs) for banknotes recognition. Especially, we have clarified its effectiveness of neurorecognition system on industrial use by implementing the neuro-recognition system to various banking machines in spite of unfocused sensing data and various noised data. Recently, another demand on banknotes recognition will be appeared. Namely, it need the more number of banknotes to be recognized at the same time on the banking machines according to appearance of Euro banknotes. In order to solve this problem, we propose a neuro-templates matching method whose templates are constructed by plural NNs. We show its effectiveness by experiments for various foreign banknotes and Euro dummy. Furthermore, we also refer extension of the proposed method to human security using bio-paratnetric information such as palmprints, fingerprints, face image and so on.First stage, we research neuro tejuplate matching as recognition algorithms. Then, we show its effectiveness with various kinds of simulation using foreign banknotes andEuro ones. At the same time, Vie re design DSP board and implement this proposed algorithms to this DSP board. Second stage, we apply this recognition algorithms and DSP board to individual recognition with pen pressure and inspection system for fallen rice. Then we show the effectiveness and usefulness of this algorithm on the real time systems.