A Review on Fake Currency Detection using Feature Extraction

Authors

  • Nikhat Yasmeen Student, Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, India
  • S. Nida Student, Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, India
  • Nishath Fathima Student, Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, India
  • Mohammad Aftab Student, Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, India
  • N. R. Deepak Professor, Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, India

Keywords:

fake currency detection

Abstract

Fake currency identification is a serious problem all around the world, affecting the economies of almost every country, including the United States. The prospective agreements are to make use of either the currency's synthetic qualities or make use of its physical look. The information presented in this study is dependent on physical conditions. The appearance of the Indian currency. It has been received those calculations are being prepared. Removing the highlights, such as security string, intaglio printing (RBI logo) and distinctive characteristics proof imprints, which have come to be accepted as Indian currency security highlights. To accomplish this, system that is becoming increasingly strong and precise. All three highlights have received a conclusive score. Intertwined to distinguish between authentic and fake monetary benchmarks The finding of counterfeit money The suggested system has an accuracy of one hundred percent. The mean square blunder, which is around 1%, is used to quantify the presentation of the proposed system. It may be accepted by ordinary persons as well, who are frequently faced with the problem of distinguishing between genuine and counterfeit monetary standards.

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Published

09-06-2022

How to Cite

[1]
N. Yasmeen, S. Nida, N. Fathima, M. Aftab, and N. R. Deepak, “A Review on Fake Currency Detection using Feature Extraction”, IJMDES, vol. 1, no. 5, pp. 30–32, Jun. 2022.

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Articles