Fake Currency Identification System Using CNN

Abstract

Fake Currency is a detrimental issue worldwide. It affects every countries economy in a linear manner. Huge Amounts of loss could occur if the fake distribution of such currency takes place. In today’s times, this is a global issue. In this system we are going to develop a fake currency detection system to discover the paper forged currency to check whether it is original or not. Identifying the fake currency is very difficult since it is made from such intricate details. One of the best methods to spot fake currency is by using software that is user-friendly and effective. In our project, we will identify Indian banknotes using a webcam’s real-time image. In this setup, a novel Complication Neural Network technique to the identification of counterfeit money notes using their photographs is studied. This approach is based on Deep Learning, which has recently had great success in image bracket challenges. The first false notes gradually increased the delicateness of the planned mechanism. The fake currency may be a severe problem for the entire world, affecting the economies of almost every nation. One of the ways through which fake currency can be found out is through camera lenses or computer web-cams. Our project with CNN methodology will help overcome this issue by scanning the notes details and analyzing the key elements through which we can tell the authenticity of the note, the use of counterfeit currency is one of the biggest problems most nations face globally. The inauthentic currency hard to trace or recognize due to their use is extremely advance technology. Most of the technologies currently in use were created using image processing techniques to identify counterfeit money. So, as part of this ground plan, we are creating a system that can identify counterfeit money using convolution neural networks (CNN).