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A Survey on Banknote Recognition Methods by Various Sensors.

Ji Woo Lee1, Hyung Gil Hong2, Ki Wan Kim3

  • 1Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. ljwgs@dongguk.edu.

Sensors (Basel, Switzerland)
|February 18, 2017
PubMed
Summary

Real money transactions are vital, with automated machines essential for processing. This review covers banknote recognition, counterfeit detection, serial number recognition, and fitness classification, highlighting techniques and challenges.

Keywords:
banknote recognitioncounterfeit banknote detectionfitness classificationserial number recognitionvarious sensors

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Area of Science:

  • Computer Vision
  • Sensor Technology
  • Financial Technology

Background:

  • Despite the rise of electronic transactions, physical currency remains significant globally.
  • Automated machines like ATMs and banknote counters are crucial for efficient and secure real money handling.

Purpose of the Study:

  • To comprehensively review banknote recognition techniques across four key areas: denomination, counterfeit detection, serial number recognition, and fitness classification.
  • To analyze the advantages and disadvantages of various sensor-based methods used in automated banknote processing.
  • To identify technological challenges and future research directions in accurate banknote recognition.

Main Methods:

  • Review of existing studies on banknote recognition using diverse sensors.
  • Analysis of techniques for extracting banknote information (denomination, serial number, authenticity, physical condition) from image and sensor data.
  • Evaluation of methods applied in real-world banknote processing machines.

Main Results:

  • Banknote recognition techniques leverage image and sensor data for accurate information extraction.
  • Existing methods are applied globally in banknote processing machines.
  • The paper provides a consolidated overview of the state-of-the-art in the four reviewed areas.

Conclusions:

  • Accurate banknote recognition is critical for automated financial transactions.
  • Technological advancements are needed to overcome current challenges in banknote processing.
  • Future research should focus on enhancing the accuracy and robustness of banknote recognition systems.