Open AccessROI based Indonesian Paper Currency Recognition Using Canny Edge Detection
Author(s) -
Ahmad Imam Rauyani,
Muhammad Hamka Ibrahim,
Subuh Pramono
Publication year - 2020
Publication title -
journal of electrical, electronic, information and communication technology (online)
Language(s) - English
Resource type - Journals
ISSN - 2715-1263
DOI - 10.20961/jeeict.2.1.41349
Subject(s) - canny edge detector , computer science , artificial intelligence , currency , edge detection , computer vision , python (programming language) , image processing , template matching , region of interest , image (mathematics) , economics , operating system , monetary economics
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 1 Indonesia banknotes which then the currency value will appear in the value variable in python.