Paper Money Recognizer Using Feature Descriptor

Nur Hadisukmana, Adri Yudianto


People are still using paper money for daily transaction; this, however, will expose some difficulty for visually impaired people. Though they can still read the nominal value of the paper money by the other people or feel the tactile feature, they cannot depend upon others all the time and the tactile feature does not work well if the paper money is worn out. Some alternatives have been proposed and conducted. One of them is using money value recognition application. The application will recognize nominal value of paper money comparing the image of the paper with database. This process is using a feature extraction algorithm called ORB feature descriptor. It has been used for six (6) different types of currencies that are 5 most traded currencies and Indonesia currency and also for different types of nominals (bills).


Computer Vision, Feature Detector, Feature Descriptor, Feature Matching, Paper Money

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