AN EFFICIENT DETECTION OF FAKE CURRENCY KNN METHOD

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.

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.

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.

International Journal of New Media Technology (IJNMT), 2019

The existence of counterfeit banknotes is often troubling the public. The solution given by the government to be careful of counterfeit banknotes is by means of 3D (seen, touched and looked at). However, this step has not been perfectly able to distinguish real banknotes and fake banknotes. So, there is a need for a system to help detect the authenticity of banknotes. Therefore, in this study a system was designed that can detect the authenticity of rupiah banknotes and its nominal value. For data acquisition, this system uses detection boxes, ultraviolet lights and smartphone cameras. As for feature extraction, this system uses segmentation methods. The segmentation method based on the threshold value is used to obtain an invisible ink pattern which is a characteristic of real banknotes along with the nominal value of the banknotes. The feature is then used in the stage of detection of banknotes authenticity using FKNN (Fuzzy K-Nearest Neighbor) method. From 24 test data, obtained an average accuracy of 96%. This shows that the system built can detect the authenticity and nominal value of the rupiah banknotes well.

International Journal of Emerging Trends in Engineering Research, 2021

Fake Currency Detection is the biggest problem faced by many countries including India. The advancement of colour printing technology has increased the rate of fake currency note printing and duplicating the notes on a very large scale. So, it has become a necessity to develop a tool that detects the fake currency note in a less time and in a more efficient manner using Image processing.

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.

International Journal of Computer Graphics, 2020

We propose a technique for web access by infusing or embeddings ordering different nations notes. An Image is separating and preparing procedure to recognize and match the distinguished information required cash picture and the first reference picture, each money note taken a Region of Interest (ROI) on existing money note condition. A separated cash picture ROI can be utilized to different example development and acknowledgement procedures and ANN hubs recognizing systems. At once, numerous cash notes are distinguished by coordinated notes then a web seek based following framework to recognize coordinating procedure is allowed for getting to for their specified timeframe. At first, we secure required the cash note by average level picture scanner on settled dpi shading with a required size arrangement; the dpi pixels level is set to get an ordinary picture utilizing picture preparing strategy. Barely any cutting edge picture channels are connected to proposed picture remarkable estimation of required cash take note of, this relegated esteem or images are contrasted and the doled out info sign images to coordinate unique note esteem, at that point web-based getting to technique controls by the microcontroller to examine all prerequisite fields and fundamental activities. 1

IJCSMC, 2019

Fake Currency has always been an issue which has created a lot of problems in the market. The increasing technological advancements have made the possibility for creating more counterfeit currency which are circulated in the market which reduces the overall economy of the country. There are machines present at banks and other commercial areas to check the authenticity of the currencies. But a common man does not have access to such systems and hence a need for a software to detect fake currency arises, which can be used by common people. This proposed system uses Image Processing to detect whether the currency is genuine or counterfeit. The system is designed completely using Python programming language. It consists of the steps such as grayscale conversion, edge detection, segmentation, etc. which are performed using suitable methods.

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 & Engineering Technology (IJRASET), 2022

Counterfeit money has always existed an issue that has caused many problems in the market. Technological growth development has made it possible to create extra counterfeit items which are distributed in the mitigation market the global economy. Bangui existing banking equipment and so on trading sites to check the authenticity of funds. But the average person does not do that have access to such systems and that is why they are needed in order for the software to receive counterfeit money, which can be used by ordinary people. This the proposed system uses image processing to find out if the money is real or fake. System built uses the Python system completely language. It contains similar steps grayscale modification, edge detection, separation, etc. made using appropriate methods.

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.

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.

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...

— 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.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2024

This project aims to develop a robust fake currency detection system leveraging image processing and machine learning techniques. Data cleaning involves image quality enhancement and handling of torn or dirty notes. The experimental setup includes a digital camera in a controlled lighting environment to capture currency images. MATLAB is used for software setup due to its extensive libraries.