A Hybrid Technique for Fake Currency Detection

Abstract

Indian currency consists in many different forms such as coins, banknotes etc. Fake or counterfeit currency notes are a major problem worldwide and India is also effected by the counterfeit banknotes. The Indian government is well aware of this threat and has started taking counter effective measures. Recently demonetisation of 1000 and 500 Rupee currency notes have been done and the 1000 Rupee banknote was replaced by 2000 Rupee banknote. The newly released banknotes are much more safe and hard to reproduce as compared to their old versions. Every denomination of Indian banknotes such as 10,100, 200, 500 etc has been renewed with better security features to insure more security but after all these measures fake Indian currency notes are being produced both locally and across the border, which is a serious problem as it helps in deteriorating economy of the our country. In this paper our main aim is to create a hybrid approach consisting of Digital Image Processing, Feature Extraction of Indian currency notes. Then clustering is performed followed by classification and comparing them with fake examples. Which will help us in detecting the fake Indian currency notes and hence further stopping the circulation of these counterfeits in our country.