Indian Paper Currency Recognition using Image Processing

India is a developing country, Production and printing of Fake notes of Rs.100, 500 and 1000 are degrading financial increase of our country. From last few years due to technological advancement in color printing, duplicating, and scanning, counterfeiting troubles are coming into picture. In this article, recognition of paper currency with the help of digital photo processing methods is described. Around eight traits of Indian paper currency is selected for counterfeit detection. The identification marks, optical variable link, see via register and currency colour code decides the currency recognition. The end result will predict whether or not the currency note is genuine or not. Gray level co-occurrence matrix is formulated to obtain statistical texture features. A number of texture features may be extracted from the GLCM. Only four second order features namely contrast, correlation, energy, homogeneity are computed. These four measures provide high discrimination accuracy required for motion picture estimation. The Gray Level Co-occurrence Matrix (GLCM) method is a way of extracting second order statistical texture features. This approach has been used in a number of applications.