ROI based Indonesian Paper Currency Recognition Using Canny Edge Detection

Ahmad Imam Rauyani, Muhammad Hamka Ibrahim, Subuh Pramono


Paper currency recognition is important for automatic payment system. The paper performs a nominal paper detection process using image processing with canny method implemented in python programming language. The canny method is used to find edge features in the nominal currency. By using template matching of image reference, region of interest (ROI) of nominal value is extracted so that it can be used in any orientation of  paper currency image. The ROI of nominal image is processed by canny edge method and spatial transformation to strengthen the image features and being processed by template matching to decide nominal currency. The study has successfully tested nominal value of 1000, 2000, 5000, 10000, 20000, 50000, and 100000 Indonesia banknotes which then the currency value will appear in the value variable in python.

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