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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...
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...
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.
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 processing .This technique is considered with the computer vision where all processing with the image is done by machine. The machine is fitted with a camera (scanner) 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 character recognition methods. To implement this design we are dealing with MATLAB Tool.
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.
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...
Journal of emerging technologies and innovative research, 2019
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 money identification, so just real money are expected to prepare the classifier.Our country is a developing economy and creating a nation, generation, the printing of case duplication of 100 notes, 500 notes, 200 notes, and 2000 notes are debasing and falling apart the monetary development of our nation. From the most recent couple of years on account of innovative headway in shading printing, copying, and filtering, falsifying issues are coming into the picture. The acknowledgment of paper cash with the assistance of Arduino based innovation methods is portrayed.
In cash transactions, the biggest challenge faced is counterfeit notes. This problem is only expanding due to the technology available and many fraud cases have been uncovered. Manual detection of counterfeit notes is time consuming and inefficient and hence the need of automated counterfeit detection has raised. To tackle this problem, we studied existing systems using Matlab, which used different methods to detect fake notes.
IRJET, 2022
The global economy is vulnerable to counterfeit currency. Advanced printing and scanning technologies have made it a common occurrence. For both people and corporations, fake currency recognition is a serious issue. The creation of counterfeit banknotes, which are barely distinguishable from legitimate currency, is a continuous process for counterfeiters. To detect fake notes, several traditional techniques and approaches are available based on colors, widths, and serial numbers. This paper discusses different methods of fake currency detection using image processing.
International Journal of Trend in Scientific Research and Development, 2018
Nowadays problem of fake currency increases because of increasing in technology like scanning, color printing so result in counterfeit currency. In India increase in fake paper currency notes of 100, 500, 2000 rupees etc. So detection of fake currency is n The determination of fake currency with the help of image processing. Firstly Image acquisition is done then pre-processing stage applied to that image for suppress unwanted feature and added some feature which are necessary for further process. Conversion of RGB picture into HSV scale. Then image segmentation applied to that image in this image divided into number of objects. Then morphological operation is perform on that picture. Further feature extraction/area of calculation stage applied to that picture and finally that picture compared with the original image.
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 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.
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.
IRJET, 2020
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 detection is up to 95.0% and tested this method on different denominations of Indian banknote.
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 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.
Automatic currency recognition and authentication has become an impending challenge today particularly because of the prevailing fraudulent activities as it hampers our economy. According to the RBI report 435,607 fake notes has been detected in year 2010-2011 and the number is only increasing with technological advancements in the field of printing. Image processing techniques such as texture based, pattern or color based, character recognition etc using different operator or tools such as Prewitt or Sobel or Canny edge detector, ANN, heuristic analysis, SVM etc are commonly used for recognition and authentication of paper currency note. Despite several researches it still remains an open challenge. This paper intends to present an extensive survey of the recent technological trends in recognition and authentication of paper currency note while identifying the various challenges.
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.
International Journal of Engineering Research and
The main objective of this project is fake currency detection using the image processing. Fake currency detection is a process of finding the forgery currency. After choose the image apply preprocessing. In pre-processing the image to be crop, smooth and adjust. Convert the image into gray color. After conversion apply the image segmentation. The features are extracting and reduce. Finally compare the image into original or forgery.
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.
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