ABSTRACT
Modernization of the financial system is a milestone in protecting the economic prosperity, and maintaining social harmony. The Reserve Bank of India is only one which has the full authority to issue bank notes in India. But some unsocial group of people is prone to make these fake currencies. Fake Indian Currency of 100, 500 and 1000 seems to have flooded the system and there is no proper way to deal with them for a common person. Common Person fall prey to this currencies. The value of money is increasing and Rs. 1000 and Rs. 500 is the highest value currency existing till date and maximum fake is done in them. From few years, along with the original currency, Fake Currency is also circulating in the society and unbalancing the social harmony of the society. Fake Currency Detection
Many of the transaction are also carried out with it. Fake currency detection means finding fake currency from the currencies. With the advancement of the modern banking services, automatic methods for paper currency detection has become important in most of the applications such as in automated teller machines and automatic goods seller machines. Images are processed by using various techniques of image processing and further various features are extracted from the images. Automatic methods of banknotes recognition are required in many applications, such as automatic selling goods and vending machines, among others. The approach consists of a number of components including image processing, image segmentation, characteristic extraction, comparing images. The basic thing of approach is that we extract the features on the basis of which we are going to classify the fake note.
The Reserve Bank is only one which has the sole authority to issue bank notes in India. Reserve Bank, like other central banks the world over, changes the design of bank notes from time to time. Traditionally, anti-counterfeiting measures involved including fine detail with raised intaglio printing on bills which allows non-experts to easily spot forgeries. On coins, milled or marked with parallel grooves edges are used to show that none of the valuable metal has been scraped off. Reserve bank uses several techniques to detect fake currency.
This counterfeiting is so famous such that it is considered as second world profession in earlier days. Coinage of money began in the Greek city of Lydia around 600 B.C. Before the introduction of paper money, the most prevalent method of counterfeiting involved mixing base metals with pure gold or silver. A common practice was to “shave” the edges of a coin. This is known as “CLIPPING”. Every year, millions of “fake” notes are passed over retail counters and the majority is not identified as counterfeit until they’re examined by the bank. Most often, retail associates don’t know how to identify legitimate money or they rely on the simplest of all anti-counterfeiting tools; the counterfeit pen. Unfortunately, relying on the pen alone is not going to catch anyone other than an amateur who is printing money on a laser printer.
Common man became a scapegoat for the fake currency circulation, let us suppose that a common man went to a bank to deposit money in bank but only to see that some of the notes are fake, in this case he has to take the blame. Counterfeiting, of whatever kind, may be that has been occurring ever since humans grasped the concept of valuable items, and there has been an ongoing race between certifier like (banks, for example) and counterfeiter ever since. Some of the effects that counterfeit money has on society include a reduction in the value of real money; and inflation due to more money getting circulated in the society or economy which in turn dampen our economy and growth – an unauthorized artificial increase in the money supply; a decrease in the acceptability of paper money; and losses. And this some of the methods to detect fake currency are water marking, optically variable ink, security thread, latent image, techniques like segmentation and using MATLAB.
Any DIR method that can produce a diffeomorphic mapping can be employed in DIRBoost.We define the interface of a DIR method:
with IF ; IMi the image pair to be registered, un a displacement field to initialize the deformable registration, and unþ1 the obtained displacement field resulting from the current registration. In DIRBoost we distinguish between the base registration (iteration n ¼ 0) and the actual boosting registration starting at n ¼ 1. Hence, the output displacement field of the base registration, u1, is the initial input displacement field for boosting. Next to a DIR method, DIRBoost requires a method for registration error detection, RED.