IRJET- INDIAN FAKE CURRENCY DETECTION USING COMPUTER VISION

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 of Research, 2015

Two qualities of Indian paper money are chosen for fake discovery included recognizable proof imprint and coin serial number. The attributes extraction is performed on the picture of the coin and it is contrasted and the qualities of the certified money. The money will be checked by utilizing picture preparing methods. The procedure of shrewd edge discovery calculation is utilized for edge recognition. The methodology comprises of picture handling, dim scale change, edge recognition, picture division, trademark extraction, looking at pictures. Keywords: Fake currency; Canny Operator; Digital image processing; imitation detection.

IRJET, 2020

In India, money transactions are increasing by the day. These increasing transactions become a cause to increase the currency traverse. Taking advantage of this, fake currency notes of Rs 50,100,500,1000 were being produced, and after demonetization the counterfeit notes of new Rs 50,200,500,2000 have increased a lot and this in time affects the economic growth of the country. Here, the recognition and verification of the paper currency is explained with the use of image processing techniques. The proposed approach consists of multiple element transactions like Image Acquisition, Feature extraction and comparison, Texture features, and Voice output. The desired results will be in text and voice output of the currency recognized and verified. Thus we can help in reducing the accumulation of counterfeit currency.

Indian is a developing country, Production and printing of Fake notes of Rs.100, 500 and 1000 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. In this article, recognition of paper currency with the help of digital image processing techniques is described. Around eight characteristics of Indian paper currency is selected for counterfeit detection. The identification marks, optical variable link, see through register and currency color code decides the currency recognition. The security threads, water mark, Latent image and micro-lettering features are used for currency verification. The characteristics extraction is performed on the image of the currency and it is compared with the characteristics of the genuine currency. The currency will be verified by using image processing techniques. The approach consists of a number of components including image processing, edge detection, image segmentation and characteristic extraction and comparing images. The desired results shall verify with MATLAB software.

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.

2020

The production of counterfeit paper currencies has become cheaper because of the advancement in the printing technologies. The circulation of counterfeit currencies down the economy of a country. By leveraging this, there is a mandate to develop an intelligent technique for the detection and classification of counterfeit currencies. The intelligent techniques play a major role in the field of Human Computer Interaction (HCI) too. This paper deals with the detection of counterfeit Indian currencies. The proposed method feature extraction is based on the characteristics of Indian paper currencies. The first order and second order statistical features are extracted initially from the input. The effective feature vectors are given to the SVM classifier unit for classification. The proposed method produced classification accuracy of 95.8%. The experimental results are compared with state-of-the methods and produced reliable results.

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...

— The issue of efficiently distinguishing counterfeit banknotes from genuine ones via automatic machines has become more and more important. This proposed system describes an approach for verification of Indian currency banknotes. Fake Indian currency of 100, 500 and 1000 rupees seems to have flooded the whole system and there is no proper way to deal with them for a common person. There is a need to design a system that is helpful in recognition of paper currency notes with fast speed and in less time. The recognition system is composed of two parts. The first is preprocessing, including detecting edges, compressing data dimensionalities, and extracting features. The second one is comparison with the pre stored database. The result is displayed by the glow of led. In order to make system complete, we need to maintain a database for storing the characteristics of the currencies.The result will be whether currency is genuine or counterfeit and the efficiency of our system is approximately 95% which can be further increased using more advanced techniques and researches. Furthermore, some related applications and the suggestions of the further work are discussed.

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.

International Journal of Engineering Sciences & Research Technology, 2013

By expansion of modern banking services, automatic schemes for paper currency recognition are significant in many applications..Automated paper currency recognition system can be a very good utility in banking systems and other field of commerce. Since many years counterfeiting of paper currency challenges the financial system of every country in different sectors, India is also one of them. In this article, various methods for the recognition of paper currency is described. An efficient currency recognition system is vital for the automation in many sectors such as vending machine, rail way ticket counter, banking system, shopping mall, currency exchange service etc. A successful approach for currency recognition depends upon feature extraction of that currency image. In this survey, we empirically demonstrate the different techniques of Indian currency notes to recognition of currency notes.

International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), Volume 8 Issue 5, pp. 21-26, July-August 2021. (UGC Journal No: 64718), 2021

India is a developing country, Creation, and print of counterfeit currency of Rs.100, 500 and 1000 is by now there but after demonetization, the counterfeit notes of new Rs.50, 200, 500, 2000 have also come darkness in very tiny time and which achieve the country’s monetary growth. From few years due to technological improvement in color printing, duplicating, and scanning, counterfeiting troubles are coming into the picture. In this a work, recognition and confirmation of paper notes with the help of digital image processing technique is described. The personality insertion is perform by picture of notes and it compared by the character of the real notes. The notes will be predictable and verified by using image processing techniques. The move toward consists of works including image processing, edge detection, image segmentation and characteristic extraction and comparing images. The preferred outcome will be text output of the notes recognized and confirmed.

2020

As of late, a ton of illicit forging rings make and sell counterfeit coins, and simultaneously counterfeit note cash is also printed, which have made incredible misfortune and harm the general public. Along these lines, it is basic to have the option to identify counterfeit cash. We propose another way to deal with identify counterfeit Indian notes utilizing their pictures. A cash picture is spoken to in the disparity space, which is a vector space developed by contrasting the picture and a lot of models. Each measurement quantifies the uniqueness between the picture viable and a model. To get the uniqueness between two pictures, the neighborhood key focuses on each picture are recognized and depicted. Because of the attributes of the cash, the coordinated key focuses on the two pictures can be recognized effectively. A post preparing strategy is additionally proposed to evacuate bungled key focuses. Because of the predetermined number of phony cash, SVM is directed for counterfeit ...

2018

Currency and counterfeiting are two different aspects of every economy .The growing hazard of mock or fictitious currency is one of the serious issues in India and also world-wide. Security features are the various authenticating measures that have been incorporated in the Indian currency notes in order to protect them for counterfeiting. In this paper, currency recognition is explored and also represented a comprehensive review of the existing literature techniques related to Indian Currency Recognition. The currency will be verified by using image processing techniques like image acquisition, pre-processing and image enhancement. The main aim of image enhancement is to identify the secret information that is hidden which cannot be visible to eye. It improves the visual appearance of a currency for human viewing, by removing blurring and noise, increasing contrast, and revealing details. The objective of this paper is to detect hidden information that are invisible to eye which hel...

IRJET, 2021

The characteristics of paper notes vary from country to country. Currency authenticity or say identification is one among the important applications of pattern recognition. We have proposed a system for the automation of currency recognition using image processing techniques. The proposed system can be used for recognizing as well as authenticating given Indian banknotes. Only paper currency will be considered. This method works by identifying certain predefined areas of interest, and then extracting the denomination value using various characteristics such as color and text on the note. Our system identifies currency quickly and accurately. Initially, our system will be taking the frontside and backside of the currency(your note) as an input and then crop it into specific predefined areas of interest. Then each image is divided into three channels. Filtering is applied to each channel, the red, green, and blue channels are recombined to get back the RGB image. Different features such as HSV are extracted from the RGB image. The proposed model is based on a feature extraction and k-Nearest Neighbor (k-NN) classifier for recognizing test banknote. The recognition system indicates that the proposed approach is one among the foremost effective strategies for identifying currency patterns to read its face value and determine its authenticity for Indian currency notes.

International Journal of Advance Research, Ideas and Innovations in Technology, 2019

Around 150+ currencies exist in the world. Each currency differs from the other on the basis of size, paper, colors, patterns, text, etc. It is difficult to identify all the currencies that exist. Also, it is difficult to determine whether a currency is real or fake. Our system proposes to tackle this problem using Image Processing in MATLAB. The different types of currencies from the different origin are provided to the system and system then performs Image Processing operations depending on the currencies and provide the identified currency type as an output. Also to authenticate currency is real or fake it performs Image Processing functions and identifies the currency provided as an input is real or fake.