Fake Currency Detection System

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...

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.

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...

Zenodo (CERN European Organization for Nuclear Research), 2023

A huge deal of counterfeit currency has been printed recently, which has hurt society greatly. Therefore, the creation of a method to identify fraudulent currency has become essential. By using their image, our proposed system will employ a method to identify counterfeit cash notes traded in our nation. Our work will offer the necessary adaptability and compatibility for the majority of individuals, as well as dependable accuracy for the detection of counterfeit currencies. To make this application effective, we are employing the logistic regression algorithm. Using a machine learning algorithm, this work will identify several significant properties in notes that will establish the currency note's uniqueness. This application makes it simple to spot fraudulent notes and reduces their availability on the market.

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

The main purpose of this project is to obtain a false-positive income using Machine Learning. This process can be automated on mobile using the application software. Basic logic is developed using image acquisition, image segmentation, feature extraction and comparison. Enlarged images of the real currency are transferred to the Machine learning dataset. The features of the note to be tested are compared to a dataset made from an actual enlarged image and determine whether it is real money or fake. The most important challenge is to repeat the systematic and systematic review process to reduce error and time. In recent years, a large number of counterfeit coins have been printed & at the same time other illegal rings are producing and selling counterfeit coins, resulting in massive loss and damage to society. So, it is a color to be able to get fake money. We propose a new proposal for obtaining fake Indian notes using their images. A coin image is represented in a space of differences, which is a vector space created by comparing an image with a set of real money proteins. Each scale measures the differences between the image presented and the model presented. In order to find the differences between the two images, the key points of the location of each image are identified and explained. Based on the characteristics of the currency, the corresponding key points between the two images can be clearly identified. The posting process is also proposed to remove key points. Due to the limited number of non-real-world funds, SVM is designed to detect fake cash, so only real money is needed to train a classifier.

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

The use of technology has grown tremendously within the few years it has made it easier to have access to advanced printing equipment in the industry which resulted in color printing of currencies to produce counterfeit notes across the country. To eliminate such unethical activities of printing counterfeit currency it is mandatory to make a system that detects the fake currency, In systems such as a money exchanger for example ATMs and vending machines, counterfeit currency notes must be detected beforehand exchanging process takes place. In the past, there have been similar systems developed based on methods such as image processing techniques that are done on the Matlab platform and other such platforms these methods possess some limitations including being less efficient and time-consuming. Our system is designed to eliminate all of the above problems through the use of deep learning techniques by detecting the features of currencies and determining whether its fake with a great accuracy rate. our proposed system verifies the Indian currency notes using Deep learning, deep learning helps in extracting meaningful information from the dataset fed into the machine using a set of methods to perform the classification of images. Our project makes use of the deep learning framework TensorFlow and its high-level API Keras which simplifies the creation of the model making it easier to achieve a less time-consuming and accurate model.

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 .

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...

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.

— 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.

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.

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...