Develop an Efficient Algorithm to Recognize and Detect Indian Currency from Image by using MATLAB

There is Great technological advancement in printing and scanning industry made counterfeiting problem to grow more vigorously. As a result, counterfeit currency affects the economy and reduces the value of original money. Thus it is most needed to detect the fake currency. Most of the former methods are based on hardware and image processing techniques. Finding counterfeit currencies with these methods is less efficient and time consuming. To overcome the above problem, we have proposed the detection of counterfeit currency using a deep convolution neural network. Our work identifies the fake currency by examining the currency images. The transfer learned convolution neural network is trained with two thousand, five hundred, two hundred and fifty Indian currency note data sets to learn the feature map of the currencies. Once the feature map is learn the network is ready for identifying the fake currency in real time. The proposed approach efficiently identifies the forgery currencies of 2000, 500, 200, and 50 with less time consumption.