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Banknote Issuing Country Identification Using Image Processing and Neural Networks

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13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 (ICAFS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 896))

Abstract

The work in this paper investigates developing an identification system for 21 countries using images of their banknotes and neural network classifiers. We consider the banknotes of 19 Asian countries, the European Union (EU), and the USA. Our motivation to investigate the Asian currencies is the increased global interaction in tourism and international trading with these countries where they have diverse and impressive banknote designs; thus making it difficult to identify by foreign visitors or traders. Our database comprises 504 original and pre-processed images of 6 banknotes of each of the 21 currencies. The investigated 19 Asian countries in this work are Afghanistan, Armenia, Azerbaijan, Bangladesh, Bhutan, Brunei, Burma, Cambodia, China, India, Kuwait, Maldives, Pakistan, Saudi Arabia, Sri Lanka, Syria, Tajikistan, Turkey, and United Arab Emirates. Most existing banknote identification systems aim to identify the currency value or decide whether a banknote is counterfeit. Our presented work is novel as it focuses on identifying the issuing country. Furthermore, we apply two pattern-averaging methods using (5 × 5) and (10 × 10) kernels, and follow two learning schemes to train and test the proposed neural identification models by using (50:50) and (75:25) training-to-validation data ratios. The obtained experimental results are considered as successful.

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Author information

Authors and Affiliations

  1. European Centre for Research and Academic Affairs (ECRAA), Nicosia, Mersin 10, Turkey

    Adnan Khashman & Waleed Ahmed

  2. Final International University, Kyrenia, Mersin 10, Turkey

    Adnan Khashman & Waleed Ahmed

  3. University of Kyrenia, Kyrenia, Mersin 10, Turkey

    Sadig Mammadli

  4. Odlar Yurdu University, AZ1008, Baku, Azerbaijan

    Sadig Mammadli

Authors
  1. Adnan Khashman
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  2. Waleed Ahmed
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  3. Sadig Mammadli
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Corresponding author

Correspondence to Adnan Khashman .

Editor information

Editors and Affiliations

  1. Joint MBA Program, Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Rafik A. Aliev

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  4. Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA

    Mo. Jamshidi

  5. Department of Mechatronics, Near East University, Nicosia TRNC, Turkey

    Fahreddin M. Sadikoglu

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Khashman, A., Ahmed, W., Mammadli, S. (2019). Banknote Issuing Country Identification Using Image Processing and Neural Networks. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_98

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