In recent years it has become a very essential to develop an automatic methods for paper currency recognition as its  more likely to be used in most of the areas such as vending machines, shopping centers, educational sectors, banking systems- in case of huge transactions and so on. As the technology  is growing  fastly  it has become more easy to use such systems. Now-a-days using automated machines any one can easily get to know whether the currency is a genuine or counterfeit and also the denomination of that currency. The technology has also provided a better way of life for peoples. There is a need to design a system that is helpful in recognition of paper currency notes with fast speed and in less time. This approach basically provides an easy method for recognizing the denomination of an Indian currency note .This proposed approach works on all the notes such as Rs.10, Rs,20, Rs.50, Rs.100, Rs.500, Rs.1000.Indian currency features such as extracting geometric shape ,denomination object are extracted from a 4*4 grid of Indian currency image. Feature extraction plays an important role in successfully achieving value/ denomination of an Indian note. The approach consists of a number of components including image acquisition ,converting RBG to HSV image ,image  pre-processing, ,Feature extraction, images are compared. The Artificial neural network is used to identify value / denomination of an Indian currency note.