Research And Implementation Of Paper Currency Technology

Notes image recognition is a popular topic in the field of pattern recognition in recent years, and it has a great future in the market. The paper currency classifier developed with this technique play a greater role in the bank role.The key technology of the classifier system is real-time image processing and image recognition. The classifier software processes the note image, and then sends the result of the paper currency to controlling system. The machine takes corresponding action to finish the classifying according to the answer. The classifier system has a high real-time requirement, it means that after notes pass the sensor, the system must output the notes information.According to different feature and real-time requirement of different notes, propose a new recognize method of combine the gridding feature and GMM, compare with the method of combine the gridding feature and distanced classifier, it is faster, and has a more high recognition rate. According to different printing of banknotes of different patterns, a new method of discriminant old or new banknotes based on notes reflective of the light of the banknotes are proposed, supply a gap of determine the old or new banknotes based on a blank area of banknotes. According to the demand of classify the incomplete-notes, an edge-based algorithm and a uniformity-based algorithm is proposed to detect the scratches and cracks appearing frequently on banknotes. According to the demand of classify the false notes, a infrared gray-based ratio algorithm and a infrared gradient-based algorithm are proposed, finding the false banknotes effectively.The experimental results show that the algorithm is able to meet classifier system.