The process of money recognition by using convolutional neural network in embeded systems

Image processing systems have entered every aspect of life. Very good successes have been achieved in cases where defective product detection is required during production control stages and requires constant attention and motivation. Open source software, Python, and embedded systems find an important place for image processing. In this way, costs are reduced and work quality is increased. In addition, with the embedded system cards used, lower energy consumption was achieved, and investment costs could be reduced. Image processing with embedded systems can be used for banknote recognition. In this master's thesis study, Raspberry Pi was used, taking into account issues such as cost, energy savings, and ease of use. Thus, the banknotes used in the Republic of Turkey was recognized with Deep Learning and Raspberry Pi. During this recognition, the relationship with light intensity was also examined, and these effects were observed through experiments.