Banknote Authentication using Random Forest Classifier

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.7 · Issue 12

Published

July 2019

Access

Open Access

Licence

CC BY-NC-SA 4.0

Rishabh Jaiswal Suhani Jaiswal

Financial institutions have adopted various automated banking systems using currency recognition as their main activity, which makes automated currency recognition of significant interest. It is difficult for humans to tell true and fake banknotes apart especially because they have a lot of similar features. Fake notes are created with precision, hence there is need for an efficient algorithm which accurately predicts whether a banknote is genuine or not. This paper proposes machine learning techniques to evaluate authentication of banknotes. A supervised classification algorithm, random forest classifier is used for differentiating genuine banknotes from fake ones. The performance of proposed research work is evaluated using certain evaluation parameters; accuracy, sensitivity and precision.

ATM Banknote BRBNMPL Data mining Random Forest Classifier

Rishabh Jaiswal, Suhani Jaiswal (2019). Banknote Authentication using Random Forest Classifier. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.7, Issue 12. ISSN: 2319-4863.

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