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http://dx.doi.org/10.7471/ikeee.2021.25.1.25

Credit Card Number Recognition for People with Visual Impairment  

Park, Dahoon (Dept. of Computer Engineering, Hongik University)
Kwon, Kon-Woo (Dept. of Computer Engineering, Hongik University)
Publication Information
Journal of IKEEE / v.25, no.1, 2021 , pp. 25-31 More about this Journal
Abstract
The conventional credit card number recognition system generally needs a card to be placed in a designated location before its processing, which is not an ideal user experience especially for people with visual impairment. To improve the user experience, this paper proposes a novel algorithm that can automatically detect the location of a credit card number based on the fact that a group of sixteen digits has a fixed aspect ratio. The proposed algorithm first performs morphological operations to obtain multiple candidates of the credit card number with >4:1 aspect ratio, then recognizes the card number by testing each candidate via OCR and BIN matching techniques. Implemented with OpenCV and Firebase ML, the proposed scheme achieves 77.75% accuracy in the credit card number recognition task.
Keywords
Card Number Recognition; Image Processing; Machine Learning; Optical Character Recognition; Region of Interest;
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