New and Old Banknote Recognition Based on Convolutional Neural Network

Abstract

Recognition for new and old currency is a key function of the paper currency sorter. How to discriminate unfitness banknotes which became rough and fuzzy, even be damaged is an important task in financial institution. Different from traditional fitness banknote recognition based on extracting feature manually, a method based on convolutional neural network was proposed to identify fitness banknotes in this paper. Firstly, we preprocess Ukrainian banknote image and train letnet-5 model to identify fitness and unfitness currency. Secondly, after optimizing the network structure from the network layer and convolutional kernel size, we determine the best structure and performance parameters. Finally, compared with the traditional fitness banknotes recognition methods, optimized structure achieves higher recognition rate. It owes better result to combining multiple features such as holes, stains and so on. In a word, the method proposed has considerable advantages in accuracy.