Classification of US Dollar Bill Money by Neuro-Pattern Recognition
Yokota Masakazu, Toshihisa Kosaka, Sigeru Omatsu · IEEJ Transactions on Electronics Information and Systems · 1995
In this paper, we propose a bill money recognition method of US dollar using a neural network. US dollar is classified into one of seven categories like 1, 2, 5, 10, 20, 50, and $100 by processing human picture contained in the US dollar. Furthemore, we transform the US dollar data into frequency domain by FFT and use amplitudes of Fourier coefficients as input data of the neural network. Recognition rate and error probability for a checking data set consisting of US dollars different from the training data set are discussed for the proposed methods.