Development of a Neuro-Templates Matching Recognition Method for Banknotes

Abstract

Up to now, Authors' research have been focussed on applications for banknotes recognition on neural networks (NNs). Especially, we have clarified its effectiveness of neuro-recognition system on industrial use by implementing the neuro-recognition system to various banking machines in spite of unfocussed sensing data and various noised data. Recently, another demand on banknotes recognition will be appeared. Namely, it is needed 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-parametric information such as palm prints, finger prints, face image and so on. 196T.

A Paper Currency Recognition System based on Neural Networks with Gaussian Functions and an Optimizing Method for Its Parameters on Way to Learning

“…Therefore, in the field of paper currency recognition, many attempts using FNN have been done [1][2][3][4][5][6][7][8]. Generally, these systems can effectively recognize the known currency patterns having been learned, even if the input data has some differences from learning samples.…”

“…In order to improve rejection capabilities of currency recognition systems, many methods such as the linear-template matching method, the multi-dimensional Gaussian probabilistic density function (PDF) method [7], and the neuro-template matching method [8] were applied. However, for the first one, although the rejection capabilities for unknown currency patterns are increased, the recognition capabilities for known currency patterns are abruptly decreased.…”