Deep Learning approaches for Automated Detection of Fake Indian Banknotes

This electronic Counterfeit currency is a major concern for governments, banks, and businesses around the world. The detection of counterfeit currency notes is a challenging task that requires sophisticated techniques to analyse various physical and security features on the notes. Traditional methods of detection are time-consuming and prone to human error. This paper proposes the use of deep learning approaches for the automated detection of counterfeit bank notes. The use of Convolutional neural networks (CNNs) to analyse currency note image features and Recurrent Neural Networks (RNNs) to analyse security features such as serial numbers is investigated. An ensemble of CNNs and RNNs is proposed to improve detection accuracy. The proposed method is tested on a dataset of genuine and counterfeit currency notes. This method outperforms traditional methods of detection in terms of accuracy and precision. Our proposed method can be integrated into existing systems to enhance the security of banknotes and protect against counterfeiting.