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Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor

In automatic paper currency sorting, fitness classification is a technique that assesses the quality of banknotes to determine whether a banknote is suitable for recirculation or should be replaced. Studies on using visible-light reflection images of banknotes for evaluating their usability have bee...

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Detalles Bibliográficos
Autores principales: Pham, Tuyen Danh, Nguyen, Dat Tien, Kim, Wan, Park, Sung Ho, Park, Kang Ryoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856040/
https://www.ncbi.nlm.nih.gov/pubmed/29415447
http://dx.doi.org/10.3390/s18020472
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author Pham, Tuyen Danh
Nguyen, Dat Tien
Kim, Wan
Park, Sung Ho
Park, Kang Ryoung
author_facet Pham, Tuyen Danh
Nguyen, Dat Tien
Kim, Wan
Park, Sung Ho
Park, Kang Ryoung
author_sort Pham, Tuyen Danh
collection PubMed
description In automatic paper currency sorting, fitness classification is a technique that assesses the quality of banknotes to determine whether a banknote is suitable for recirculation or should be replaced. Studies on using visible-light reflection images of banknotes for evaluating their usability have been reported. However, most of them were conducted under the assumption that the denomination and input direction of the banknote are predetermined. In other words, a pre-classification of the type of input banknote is required. To address this problem, we proposed a deep learning-based fitness-classification method that recognizes the fitness level of a banknote regardless of the denomination and input direction of the banknote to the system, using the reflection images of banknotes by visible-light one-dimensional line image sensor and a convolutional neural network (CNN). Experimental results on the banknote image databases of the Korean won (KRW) and the Indian rupee (INR) with three fitness levels, and the Unites States dollar (USD) with two fitness levels, showed that our method gives better classification accuracy than other methods.
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spelling pubmed-58560402018-03-20 Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor Pham, Tuyen Danh Nguyen, Dat Tien Kim, Wan Park, Sung Ho Park, Kang Ryoung Sensors (Basel) Article In automatic paper currency sorting, fitness classification is a technique that assesses the quality of banknotes to determine whether a banknote is suitable for recirculation or should be replaced. Studies on using visible-light reflection images of banknotes for evaluating their usability have been reported. However, most of them were conducted under the assumption that the denomination and input direction of the banknote are predetermined. In other words, a pre-classification of the type of input banknote is required. To address this problem, we proposed a deep learning-based fitness-classification method that recognizes the fitness level of a banknote regardless of the denomination and input direction of the banknote to the system, using the reflection images of banknotes by visible-light one-dimensional line image sensor and a convolutional neural network (CNN). Experimental results on the banknote image databases of the Korean won (KRW) and the Indian rupee (INR) with three fitness levels, and the Unites States dollar (USD) with two fitness levels, showed that our method gives better classification accuracy than other methods. MDPI 2018-02-06 /pmc/articles/PMC5856040/ /pubmed/29415447 http://dx.doi.org/10.3390/s18020472 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pham, Tuyen Danh
Nguyen, Dat Tien
Kim, Wan
Park, Sung Ho
Park, Kang Ryoung
Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor
title Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor
title_full Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor
title_fullStr Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor
title_full_unstemmed Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor
title_short Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor
title_sort deep learning-based banknote fitness classification using the reflection images by a visible-light one-dimensional line image sensor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856040/
https://www.ncbi.nlm.nih.gov/pubmed/29415447
http://dx.doi.org/10.3390/s18020472
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