Machine learning-based authentication of banknotes: a comprehensive analysis

This research investigates the utilization of machine learning techniques for the identification and classification of counterfeit currency. The study utilizes a dataset consisting of authentic and counterfeit banknotes, employing various classification algorithms to construct a robust model for automated detection. Key features, including texture, color distribution, and security attributes, are extracted to train the model, enabling a thorough analysis of banknote authenticity. The proposed system exhibits promising accuracy in distinguishing genuine currency from counterfeits, thereby enhancing security measures in financial transactions and mitigating economic fraud.

کلیدواژه ها:

Fake currency ، Counterfeit detection ، Machine Learning ، Banknote authenticity ، Economic fraud prevention