Banknote recognition based on probabilistic neural network models
Costas Nastoulis, Apostolos P. Leros, Nikolaos G. Bardis · International Conference on Systems · 2006
In the various banking systems around the world there are different types of bank notes whose classification according to their type is a time-consuming process if it is to be done manually by some person. Also such a classification done by a collaborating person usually does not provide the suitable safety required by the banking associations. In this paper we propose a new method for the problem of banknote recognition using a probabilistic neural network (PNN) which is able to proceed to the recognition even if there is an error to the input data in the order of 40%. In addition, the efficiency of the computational resources for the training period and for the recognition rate is compared with some known methods.