Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network
Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-07-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/17/7/1595 |
| _version_ | 1817995388393619456 |
|---|---|
| author | Tuyen Danh Pham Dong Eun Lee Kang Ryoung Park |
| author_facet | Tuyen Danh Pham Dong Eun Lee Kang Ryoung Park |
| author_sort | Tuyen Danh Pham |
| collection | DOAJ |
| description | Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods. |
| first_indexed | 2024-04-14T02:06:21Z |
| format | Article |
| id | doaj.art-e4342096e70b43b392a848b21feac79f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T02:06:21Z |
| publishDate | 2017-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e4342096e70b43b392a848b21feac79f2022-12-22T02:18:41ZengMDPI AGSensors1424-82202017-07-01177159510.3390/s17071595s17071595Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural NetworkTuyen Danh Pham0Dong Eun Lee1Kang Ryoung Park2Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, KoreaDivision of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, KoreaDivision of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, KoreaAutomatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods.https://www.mdpi.com/1424-8220/17/7/1595multi-national banknote classificationvisible-light banknote imagesone-dimensional line sensorconvolutional neural network |
| spellingShingle | Tuyen Danh Pham Dong Eun Lee Kang Ryoung Park Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network Sensors multi-national banknote classification visible-light banknote images one-dimensional line sensor convolutional neural network |
| title | Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network |
| title_full | Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network |
| title_fullStr | Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network |
| title_full_unstemmed | Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network |
| title_short | Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network |
| title_sort | multi national banknote classification based on visible light line sensor and convolutional neural network |
| topic | multi-national banknote classification visible-light banknote images one-dimensional line sensor convolutional neural network |
| url | https://www.mdpi.com/1424-8220/17/7/1595 |
| work_keys_str_mv | AT tuyendanhpham multinationalbanknoteclassificationbasedonvisiblelightlinesensorandconvolutionalneuralnetwork AT dongeunlee multinationalbanknoteclassificationbasedonvisiblelightlinesensorandconvolutionalneuralnetwork AT kangryoungpark multinationalbanknoteclassificationbasedonvisiblelightlinesensorandconvolutionalneuralnetwork |