Yong, Ngee Mang (2022) Deep Learning-Based Fake-Banknote Detection for The Visually Impaired People Using Light Images Captured by Smartphone Cameras. College of Engineering, Universiti Malaysia Pahang Al-Sultan Abdullah.
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EA18172_YONG_Thesis - Yong Ngee Mang.pdf - Accepted Version Download (1MB) | Preview |
Abstract
Automatic recognition of face banknotes is an important task in practical banknote handling. Research on this task has mostly involved methods applied to automatic sorting machines with multiple imaging sensors or that use specialized sensors for capturing banknote images in various light wavelengths. However, they require specialized devices. Meanwhile, smartphones are becoming more popular and can be useful imaging devices. This project will investigate and propose the best method for classifying fake and genuine banknotes using visible-light images captured by smartphone cameras based on convolutional neural networks. This project will focus on Malaysia banknotes only. Finally, the result of precision, recall and loss for this project are 0.849, 0.971 and 0.011586.
| Item Type: | Undergraduates Project Papers |
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| Additional Information: | SV: Ikhwan Hafiz bin Muhamad |
| Uncontrolled Keywords: | banknotes, visible-light images, convolutional neural networks |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | College of Engineering |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 08 Jan 2024 10:29 |
| Last Modified: | 08 Jan 2024 10:29 |
| URI: | http://umpir.ump.edu.my/id/eprint/39913 |
| Download Statistic: | View Download Statistics |
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