MBDM: Multinational Banknote Detecting Model for Assisting Visually Impaired People

Chanhum Park and Kang Ryoung Park ()
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Chanhum Park: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Republic of Korea
Kang Ryoung Park: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Republic of Korea

Mathematics, 2023, vol. 11, issue 6, 1-21

Abstract: With the proliferation of smartphones and advancements in deep learning technologies, object recognition using built-in smartphone cameras has become possible. One application of this technology is to assist visually impaired individuals through the banknote detection of multiple national currencies. Previous studies have focused on single-national banknote detection; in contrast, this study addressed the practical need for the detection of banknotes of any nationality. To this end, we propose a multinational banknote detection model (MBDM) and a method for multinational banknote detection based on mosaic data augmentation. The effectiveness of the MBDM is demonstrated through evaluation on a Korean won (KRW) banknote and coin database built using a smartphone camera, a US dollar (USD) and Euro banknote database, and a Jordanian dinar (JOD) database that is an open database. The results show that the MBDM achieves an accuracy of 0.8396, a recall value of 0.9334, and an F1 score of 0.8840, outperforming state-of-the-art methods.

Keywords: deep learning; mosaic augmentation; multinational banknote detecting model; smartphone camera; visually impaired people (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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