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Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images

Fitness classification is a technique to assess the quality of banknotes in order to determine whether they are usable. Banknote classification techniques are useful in preventing problems that arise from the circulation of substandard banknotes (such as recognition failures, or bill jams in automat...

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Autores principales: Kwon, Seung Yong, Pham, Tuyen Danh, Park, Kang Ryoung, Jeong, Dae Sik, Yoon, Sungsoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934289/
https://www.ncbi.nlm.nih.gov/pubmed/27294940
http://dx.doi.org/10.3390/s16060863
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author Kwon, Seung Yong
Pham, Tuyen Danh
Park, Kang Ryoung
Jeong, Dae Sik
Yoon, Sungsoo
author_facet Kwon, Seung Yong
Pham, Tuyen Danh
Park, Kang Ryoung
Jeong, Dae Sik
Yoon, Sungsoo
author_sort Kwon, Seung Yong
collection PubMed
description Fitness classification is a technique to assess the quality of banknotes in order to determine whether they are usable. Banknote classification techniques are useful in preventing problems that arise from the circulation of substandard banknotes (such as recognition failures, or bill jams in automated teller machines (ATMs) or bank counting machines). By and large, fitness classification continues to be carried out by humans, and this can cause the problem of varying fitness classifications for the same bill by different evaluators, and requires a lot of time. To address these problems, this study proposes a fuzzy system-based method that can reduce the processing time needed for fitness classification, and can determine the fitness of banknotes through an objective, systematic method rather than subjective judgment. Our algorithm was an implementation to actual banknote counting machine. Based on the results of tests on 3856 banknotes in United States currency (USD), 3956 in Korean currency (KRW), and 2300 banknotes in Indian currency (INR) using visible light reflection (VR) and near-infrared light transmission (NIRT) imaging, the proposed method was found to yield higher accuracy than prevalent banknote fitness classification methods. Moreover, it was confirmed that the proposed algorithm can operate in real time, not only in a normal PC environment, but also in an embedded system environment of a banknote counting machine.
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spelling pubmed-49342892016-07-06 Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images Kwon, Seung Yong Pham, Tuyen Danh Park, Kang Ryoung Jeong, Dae Sik Yoon, Sungsoo Sensors (Basel) Article Fitness classification is a technique to assess the quality of banknotes in order to determine whether they are usable. Banknote classification techniques are useful in preventing problems that arise from the circulation of substandard banknotes (such as recognition failures, or bill jams in automated teller machines (ATMs) or bank counting machines). By and large, fitness classification continues to be carried out by humans, and this can cause the problem of varying fitness classifications for the same bill by different evaluators, and requires a lot of time. To address these problems, this study proposes a fuzzy system-based method that can reduce the processing time needed for fitness classification, and can determine the fitness of banknotes through an objective, systematic method rather than subjective judgment. Our algorithm was an implementation to actual banknote counting machine. Based on the results of tests on 3856 banknotes in United States currency (USD), 3956 in Korean currency (KRW), and 2300 banknotes in Indian currency (INR) using visible light reflection (VR) and near-infrared light transmission (NIRT) imaging, the proposed method was found to yield higher accuracy than prevalent banknote fitness classification methods. Moreover, it was confirmed that the proposed algorithm can operate in real time, not only in a normal PC environment, but also in an embedded system environment of a banknote counting machine. MDPI 2016-06-11 /pmc/articles/PMC4934289/ /pubmed/27294940 http://dx.doi.org/10.3390/s16060863 Text en © 2016 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
Kwon, Seung Yong
Pham, Tuyen Danh
Park, Kang Ryoung
Jeong, Dae Sik
Yoon, Sungsoo
Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images
title Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images
title_full Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images
title_fullStr Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images
title_full_unstemmed Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images
title_short Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images
title_sort recognition of banknote fitness based on a fuzzy system using visible light reflection and near-infrared light transmission images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934289/
https://www.ncbi.nlm.nih.gov/pubmed/27294940
http://dx.doi.org/10.3390/s16060863
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