Thai Banknote Recognition Using Neural Network and Continues Learning by DSP Unit

Nowadays, neural networks (NNs) are widely used in many fields of engineering and the most famous application is pattern recognition. In our previous researches, a banknote recognition system using a NN has been developed for various applications in worldwide banking systems such as banknote readers and sorters. In this paper, a new kind of banknotes, Thai banknotes, are being proposed as the objects of recognition. First, the slab values, which are the digitized characteristics of banknote by the mask set, are extracted from each banknote image. These slab values are the summation of non-masked pixel values of each banknote. Second, slab values are inputted to the NN to execute its learning and recognition process. Third, for commercial usability, the NN algorithm is implemented on the DSP unit in order to execute the continuous learning and recognition. We show the recognition ability of the proposed system and its possibility for self-refreshed function on the DSP unit using Thai banknotes.