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Sensors 2018, 18(2), 472; https://doi.org/10.3390/s18020472

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

Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea
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Received: 12 January 2018 / Revised: 30 January 2018 / Accepted: 1 February 2018 / Published: 6 February 2018
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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Abstract

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. View Full-Text
Keywords: fitness classification; deep learning; reflection images of banknote; visible-light one-dimensional line image sensor; convolutional neural network fitness classification; deep learning; reflection images of banknote; visible-light one-dimensional line image sensor; convolutional neural network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Pham, T.D.; Nguyen, D.T.; Kim, W.; Park, S.H.; Park, K.R. Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor. Sensors 2018, 18, 472.

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