Automatic Indian New Fake Currency Detection Technique

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...

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...

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...

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.

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 ...

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.

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.

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.

2018

Since last few years, as a result of the great technological advances in color printing, duplicating and scanning, counterfeiting problems have become more and more serious. In the past, only the printing house has the ability to make counterfeit note, 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 the issue of efficiently verifying counterfeit banknotes from real ones via automatic machines has become more and more important. Counterfeit notes are a problem of almost every country but India has been hit really hard and has become a very acute problem. There is a need to design a system that will helpful for recognition of paper currency notes with fast speed and in less time. This proposed system describes an approach for verification of Indian banknotes. The currency will be checked out by using image processing techniques. The approach consists of a number of elements including processing ...

2021

Malpractising has always been a serious challenge that resulted in a serious problem in society. The automation in technology creates a more copied currency that is entirely spread, resulting in reducing the economic growth of the country. The note detection is compulsory, and also necessary to be very consistent and reliable. The paper currency identification depends upon a number of steps, including edge detection, feature extraction, image segmentation, grayscale conversion, and comparison of images. This paper also consists of a literature survey consisting of different methodologies for detection. The review to detect malpractice concludes that whenever we apply some efficient preprocessing and feature extraction techniques, it helps in improving the algorithm as well as the detection system. Machine Learning techniques help in building tools that is required and necessary for the research work, and we can make computer learning design, implementation, and methods to have a dif...

— 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.

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.

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...

IFIP Advances in Information and Communication Technology, 2013

Counterfeit currency varies from low quality color scanner/printer-based notes to high quality counterfeits whose production is sponsored by hostile states. Due to their harmful effect on the economy, detecting counterfeit currency notes is a task of national importance. However, automated approaches for counterfeit currency detection are effective only for low quality counterfeits; manual examination is required to detect high quality counterfeits. Furthermore, no automatic method exists for the more complex-and important-problem of identifying the source of counterfeit notes. This paper describes an efficient automatic framework for detecting counterfeit currency notes. Also, it presents a classification framework for linking genuine notes to their source printing presses. Experimental results demonstrate that the detection and classification frameworks have a high degree of accuracy. Moreover, the approach can be used to link high quality fake Indian currency notes to their unauthorized sources.

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.