Using a Three-layered Perceptron and RBF Networks
نویسندگان
چکیده
We propose an Euro banknote recognition system using two types of neural networks; a three-layered perceptron and a Radial Basis Function (RBF) network. A three-layered perceptron is well known method for pattern recognition and is also a very effective tool for classifing banknotes. An RBF network has a potential to reject invalid data because it estimates the probability distribution of the sample data. We use a three-layered perceptron for classification and several RBF networks for validation. The proposed system has two advantages over the system using only one RBF network. The feature extraction area can be simply defined, and the calculation cost does not increase when the number of classes increases. We also propose to use infra-red (IR) and visible images as input data to the system since Euro banknotes have quite significant features in IR images. We have tested our system in terms of acceptance rates for valid banknotes and rejection rates for invalid data.
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