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Overview of currency recognition using deep learning

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Abstract

The human visual system could be used for recognizing and authenticating currency notes. However, the observation powers of our eyes are limited, and it is often difficult for us to recognize genuine currency without any technological assistance. Deep learning techniques have shown to be effective and superior for many applications. They have been particularly successful in surpassing human visual recognition capabilities when big data is employed. Therefore deep learning has been employed to improve the accuracy of currency recognition. After studying the existing currency identification literature, we present a comprehensive overview of currency recognition. We also discuss the critical problem of augmenting the limited amount of data available. Our contributions include summarizing the deep learning approaches such as CNN, SSD, MLP, etc. We also present our attempt to apply deep learning to currency recognition, with the aim of improving the existing recognition accuracy. The paper also describes in brief the potential future directions for research.

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Authors and Affiliations

  1. Auckland University of Technology, Auckland, 1010, New Zealand

    Qian Zhang & Wei Qi Yan

  2. National University of Singapore, Singapore, 117417, Singapore

    Mohan Kankanhalli

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  1. Qian Zhang
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  2. Wei Qi Yan
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Correspondence to Wei Qi Yan.

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Zhang, Q., Yan, W.Q. & Kankanhalli, M. Overview of currency recognition using deep learning. J BANK FINANC TECHNOL 3, 59–69 (2019). https://doi.org/10.1007/s42786-018-00007-1

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