Indian Currency Detection Using KNN Classifier

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

Bank currency is our country's most valuable asset, and to cause inconsistencies in money, criminals use phony notes that seem identical to the real one on the stock exchange. During demonetization time it is seen that so much fake currency is floating in the market. In general, for a human being, it is very difficult to identify forged notes from the genuine not instead of various parameters designed for identification as many features of forged notes are similar to the original one. To discriminate between fake bank currency and original note is a challenging task. So, there must be an automated system that will be available in banks or ATMs. To design such an automated system there is a need to design an efficient algorithm that can predict whether the banknote is genuine or forged bank currency as fake notes are designed with high precision. In this paper, six supervised machine learning algorithms are applied to the dataset available on the UCI machine learning repository for the detection of Bank currency authentication. To implement this we have applied Support Vector Machine, Random Forest, Logistic Regression, Naïve Bayes, Decision Tree, K-Nearest Neighbor by considering three train test ratios 80:20, 70:30, and 60:40 and measured their performance based on various quantitative analysis parameters like Precision, Accuracy, Recall, MCC, F1-Score and others. And some SML algorithms are giving 100 % accuracy for a particular train test ratio.

International journal of engineering research and technology, 2017

In India,’ currency’ is the means of Transaction so there is more value for currency in our social and economic development. Here, currency exists in the form of coins, banknotes and electronic data. Fake money or counterfeit notes is the dangerous or acute problem in front of whole world, and India is also a part of this fake currency. Modernization in the financial system is a milestone in protecting the economic development and now a days Indian government has become conscious about this so demonetization of Rs 1000 and Rs 500 notes is the latest example of it. But again we have Rs 2000 as a new currency in market. so as the highest value note there is a chance that corrupt people will try to make it as a counterfeit. So main objective of this paper is to study different key features of new genuine currency and use such techniques to detect and verify new currency circulated by Reserve Bank Of India. There are Different techniques which are used to distinguish between counterfeit...

2020

1PG Student, Dept. Of Computer Science and Engineering, Lingaya’s Vidyapeeth, Faridabad, India 2Assistant Professor, Dept. Of Computer Science and Engineering, Lingaya’s Vidyapeeth, Faridabad, India ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract This paper developed a computer vision based approach for Indian paper currency detection. In this approach, extract currency feature and develop an own datasets used for the currency detection. By using feature extraction method of front and back side Rs. 200 denomination security feature of Indian currency note. The mainly use ORB (Oriented FAST and Rotated BRIEF) and Brute-Force matcher approach to extract the feature of paper currency, so that can more accurately detection the denomination of the banknote both obverse and reverse. Our main contribution is through using ORB and BF matcher in OpenCV based, the average accuracy of detectio...

IRJET, 2020

This paper presents the various fake currency detection techniques. Fake currency is imitation currency produced without the legal sanction of the state or government. Production and printing of Fake notes of Rs.100, 200, 500 and 2000 are degrading economic growth of our country. From last few years due to technological advancement in color printing, duplicating, and scanning, counterfeiting problems are coming into picture. So, Fake currency detection system has become more and more important. In this paper verification of fake currency note is done by the concepts of image processing. MATLAB is used to extract the features of the real and fake notes. The comparison between the features will predict whether the currency note is fake or not.

2014

In India Every year RBI (Reserve bank of India) face the problem on counterfeit currency notes.The bank staffs are specially trained to detect counterfeit notes but problem begins once such notes are mixed into the market and circulated through common people. Even receiving fake notes from ATM counters have also been reported at some places. Over the past few years, as a result of the great technology come advances in color printing, duplicating and scanning counterfeiting problems become increses. In the previous, only the printing house has the ability to make counterfeit paper currency, but today it is possible for any person to print counterfeit bank notes simply by using a computer and a laser printer at house. Therefore to stop these issue The Indian currency notes recognition system is very useful .In order to deal with such type of problems, an automated Recognition of currency notes is introduced with the help of feature Extraction, classification based in SVM, Neural Net.ANN is introduced to train the data and classify the segments Using its datasets. This technique is considered with the computer vision where all processing with the image is done by machine. The machine is fitted with a CDD camera which will scan the image of the currency note considering the dimensions of the banknote and software will process the image segments with the help of SVM and character recognition methods. To implement this design we are dealing with MATLAB Tool .

International Journal for Research in Applied Science and Engineering Technology, 2021

The Currency Recognition System was developed for the purpose of fraud detection in paper currency, so this system is u sed worldwide. The uses of this framework can be recognized in banking frameworks, cash observing gadgets, cash trade frameworks. This paper proposes an automatic paper currency recognition system through an application developed using Machine learning Algorithms. The algorithm implemented is simple, robust and efficient.

The advancement of color printing technology has increased the rate of fake currency note printing and duplicating the notes on a very large scale. Few years back, the printing could be done in a print house, but now anyone can print a currency note with maximum accuracy using a simple laser printer. As a result the issue of fake notes instead of the genuine ones has been increased very largely. India has been unfortunately cursed with the problems like corruption and black money .And counterfeit of currency notes is also a big problem to it. This leads to design of a system that detects the fake currency note in a less time and in a more efficient manner. The proposed system gives an approach to verify the Indian currency notes. Verification of currency note is done by the concepts of image processing. This article describes extraction of various features of Indian currency notes. MATLAB software is used to extract the features of the note. The proposed system has got advantages like simplicity and high performance speed. The result will predict whether the currency note is fake or not.

2021

Student Dept. of Comp. Engineering, Pillai College of Engineering, New Panvel, Maharashtra, India -----------------------------------------------------------------------***-----------------------------------------------------------------------Abstract— Fake currency is the money produced without the approval of the government, creation of it is considered as a great Offence. The elevation of colour printing technology has increased the rate of fake currency note printing on a very large scale. Years before, the printing could be done in a print house, but now anyone can print a currency note with maximum accuracy using a simple laser printer. This results in the issue of fake notes instead of the genuine ones has been increased very largely. It is the biggest problem faced by many countries including India. Though Banks and other large organizations have installed Automatic machines to detect fake currency notes, it is really difficult for an average person to distinguish between th...

2014

s In India Every year RBI (Reserve bank of India) face the problem on counterfeit currency notes. The bank staffs are specially trained to detect counterfeit notes but problem begins once such notes are mixed into the market and circulated through common people. Even receiving fake notes from ATM counters have also been reported at some places. Over the past few years, as a result of the great technology come advances in color printing, duplicating and scanning counterfeiting problems become increases. In the previous, only the printing house has the ability to make counterfeit paper currency, but today it is possible for any person to print counterfeit bank notes simply by using a computer and a laser printer at house. Therefore to stop these issue The Indian currency notes recognition system is very useful .In order to deal with such type of problems, an automated Recognition of currency notes is introduced with the help of feature Extraction, classification based on Image process...

Paper currency identification is one of the image processing techniques i.e. clothed to recognize currency of different countries. The paper currencies of different countries are collectively rises ever more. However, the main intention of most of the standard currency recognition systems and machines is on recognizing fake currencies. The features are extracted by using image processing toolbox in MATLAB and preprocessed by reducing the data size in captured image. The expose pluck out is discharged by considering HSV (Hue Saturation Value). The chief is neural network classifier and the next step is recognition. MATLAB is used to evolve this program. The new source of paper currency recognition is pattern recognition. But for currency recognition, converter system is an image processing method which is used to identify currency and transfer it into the other currencies as the users need. The need of currency recognition and converters is accurately to recognize the currencies and transfer the currency immediately into the other currency. This application uses the computing energy in differentiation among different kinds of currencies are differentiated with their suitable class using power computing. Fake note at present plays a key topic for the researchers. The recognition system is composed of two parts. First is the captured image and the second is recognition. Forged currencies recognition is the main aim of the standard paper currency identification system. The most mandatory system is currency identification system and it should be very accurate. The performance of different methods are surveyed to refine the exactness of currency recognition system.