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Detection of counterfeit banknotes by security components based on image processing and GoogLeNet deep learning network

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Abstract

This paper aims to develop a novel method to identify counterfeit banknotes using its security components based on both image processing and GoogLeNet deep learning network. To accomplish this aim, some high-precision security components have been extracted from the banknote images through image processing and machine learning algorithms. In this way, after presenting the trained model to GoogLeNet, the degree of authenticity of each security component is estimated. The proposed method is capable of identifying the security components of the original banknote via 100% accuracy and can report low accuracy for fake and invalid samples. The proposed method is more efficient and practical as compared to similar methods.

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Authors and Affiliations

  1. Department of Computer Engineering, Shafagh Institute of Higher Education, Tonekabon, Iran

    Kamran Teymournezhad & Ali Asghari

  2. Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran

    Hossein Azgomi

Authors
  1. Kamran Teymournezhad
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  2. Hossein Azgomi
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  3. Ali Asghari
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Correspondence to Hossein Azgomi.

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Teymournezhad, K., Azgomi, H. & Asghari, A. Detection of counterfeit banknotes by security components based on image processing and GoogLeNet deep learning network. SIViP 16, 1505–1513 (2022). https://doi.org/10.1007/s11760-021-02104-z

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  • DOI: https://doi.org/10.1007/s11760-021-02104-z

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