Detection of Forged Currency Notes using Machine learning algorithms
Madhav Sharma, Gaurav Joshi, Abhishek Singh, Vivek Sharma · 2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) · 2022
Currency is a medium of exchange either to purchase or sell the goods and services. In today’s world, With enhanced technology, counterfeit currency has become a concerning threat. Counterfeit currency leads to harm the country’s economy. Severe implications are such as artificial inflation, terror funding. These concerning causes destabilize the real value of money and inflation surges over its sky. Moreover, due to terror-related activities the social-harmony gets disturbed, this can be termed as "Economic Terrorism". The proposed methodology in this paper uses Random Forest & SVM Machine Learning Algorithms to classify forged currency notes The algorithms are evaluated using metrics Accuracy, Confusion Matrix and Classification Report. The results show that SVM has outperformed Random Forest by achieving an accuracy of 99.63%.