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Fake currency detection, Study Guides, Projects, Research of Machine Learning

University of DhakaMachine Learning

This document is about fake currency detection using image processing.

Typology: Study Guides, Projects, Research

2024/2025

Uploaded on 05/09/2025

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Fake Currency Detection Using Image Processing
Nure Hafsa Shefa(20CSE018)
Department of CSE, University of Barishal
Abstract—Fake currency refers to imitation money produced without legal authorization from the state or government. Producing
or using of such counterfeit money constitutes an act of fraud or forgery. Fake currency causes major issues in our economic
growth and also it will decrease the value of original money. This project proposes an approach that will detect fake currency
note being circulated in our country by using their image. It is very lengthy and confusing process to identify the currency note is
genuine or not in manual way. 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 Bangladeshi currency notes. 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 Image acquisition, gray scale conversion, edge detection, image
segmentation, feature extraction and comparison, which are performed using suitable methods.
Keywords— Counterfeit currency, Image Processing, Python programming language, gray scale conversion, edge detection,
segmentation.
1. Introduction
The detection of counterfeit currency is a serious
issue worldwide, impacting the economies of
virtually all nations, including Bangladesh. The
duplication of currency, also referred to as counterfeit
currency is a vulnerable threat on economy. It is now
a common phenomenon due to the availability of
advanced printing and scanning technologies.
Different countries around the world use different
types of currencies for the monetary exchange of
some kinds of goods. One common problem faced by
many countries related to currency, is the inclusion of
fake currency in the system. Bangladesh is one of the
countries that face a lot of problems and huge losses
due to the fake currencies. Due to this there are losses
in the overall economy of the country„s currency
value.
Commercial areas like the banks, malls, jewelry
stores, etc have huge amount of transactions on a
daily basis. Such places may be able to afford and
consider it practical to purchase machines that check
the currency's validity using UV light and other
methods. However, it can be quite difficult for the
average person to simply tell whether a currency note
is real or not, and they may suffer losses, particularly
during bank deposits or other transactions. Visitors
are the most susceptible to phony currency because
they lack the knowledge necessary to distinguish
between fake and genuine currency notes This system
is created so that anyone may use it quickly and
determine the authenticity of the money they possess
by utilizing the visual characteristics of that money.
This technology can also be turned into an
application to make it available to everyone.
Detecting of fake note some module including image
acquisition, Image per-processing, Image adjusting,
Grayscale conversion, Edge detection, Segmentation,
Feature extraction classification every step required
algorithm for which using OpenCV library ( open
source computer vision library) .
2. Project Outline
This project paper is based on Fake Currency
Detection. In “Introduction” section it includes the
introduction and objective part which mainly
describe about our project topic, why this project is
important and which methods are used in our project
to make it successful. “Literature review” section
mainly represents the summary of the different
project paper related to our project topic, including of
what they had achieved and by which process they
had done their project etc. The third section includes
the methodology part which mainly represents the
description of the process with the flow-chart
diagram, features of the currency by following we did
our project. The last part includes the conclusion part
that includes result and discussion part, which
represents what we will get from our project with the
advantages of our project and also includes
limitations of our project and the scope at which we
can improve our project in the future.
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Fake Currency Detection Using Image Processing

Nure Hafsa Shefa(20CSE018) Department of CSE, University of Barishal Abstract— Fake currency refers to imitation money produced without legal authorization from the state or government. Producing or using of such counterfeit money constitutes an act of fraud or forgery. Fake currency causes major issues in our economic growth and also it will decrease the value of original money. This project proposes an approach that will detect fake currency note being circulated in our country by using their image. It is very lengthy and confusing process to identify the currency note is genuine or not in manual way. 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 Bangladeshi currency notes. 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 Image acquisition, gray scale conversion, edge detection, image segmentation, feature extraction and comparison, which are performed using suitable methods. Keywords— Counterfeit currency, Image Processing, Python programming language, gray scale conversion, edge detection, segmentation.

1. Introduction

The detection of counterfeit currency is a serious issue worldwide, impacting the economies of virtually all nations, including Bangladesh. The duplication of currency, also referred to as counterfeit currency is a vulnerable threat on economy. It is now a common phenomenon due to the availability of advanced printing and scanning technologies. Different countries around the world use different types of currencies for the monetary exchange of some kinds of goods. One common problem faced by many countries related to currency, is the inclusion of fake currency in the system. Bangladesh is one of the countries that face a lot of problems and huge losses due to the fake currencies. Due to this there are losses in the overall economy of the country„s currency value. Commercial areas like the banks, malls, jewelry stores, etc have huge amount of transactions on a daily basis. Such places may be able to afford and consider it practical to purchase machines that check the currency's validity using UV light and other methods. However, it can be quite difficult for the average person to simply tell whether a currency note is real or not, and they may suffer losses, particularly during bank deposits or other transactions. Visitors are the most susceptible to phony currency because they lack the knowledge necessary to distinguish between fake and genuine currency notes This system is created so that anyone may use it quickly and determine the authenticity of the money they possess by utilizing the visual characteristics of that money. This technology can also be turned into an application to make it available to everyone. Detecting of fake note some module including image acquisition, Image per-processing, Image adjusting, Grayscale conversion, Edge detection, Segmentation, Feature extraction classification every step required algorithm for which using OpenCV library ( open

source computer vision library).

2. Project Outline

This project paper is based on Fake Currency Detection. In “Introduction” section it includes the introduction and objective part which mainly describe about our project topic, why this project is important and which methods are used in our project to make it successful. “Literature review” section mainly represents the summary of the different project paper related to our project topic, including of what they had achieved and by which process they had done their project etc. The third section includes the methodology part which mainly represents the description of the process with the flow-chart diagram, features of the currency by following we did our project. The last part includes the conclusion part that includes result and discussion part, which represents what we will get from our project with the advantages of our project and also includes limitations of our project and the scope at which we can improve our project in the future.

3. Literature Review

Over the year a lot of researchers have made significant contributions to the field of currency note detection. The researchers have done detection based on security feature, texture, color etc. In this section, we review previous work in currency detection techniques. Deshpande and Shrivastava [1], the propose a recognition and authentication system using image processing which can be a good for recognition the fake currency note. In this methodology, extract the security features with Multispectral imaging. They are so many feature extract in this process is Mahatma Gandhi portrait, watermark, RBI watermark , 2000 watermark, electrotype watermark of 2000 denomination note. Y. Neeraja et.al. [2], describe a fake currency detection using k-nn technique. In this methodology, the feature extraction process by k-nn technology is a robust and versatile classifier that is often used as a benchmark for more complex classifiers such as support vector machines (SVM). Sawant and More [3], introduce an approach to detect fake note using minimum distance classifier technique. In this paper, the extract an ID mark and latent image and compute the Euclidean distance between the test sample and train sample. The Fourier descriptor is used for the describe the note boundary. The experimental setup is done on rupees 20, 50, 100,500 and 1000.The average success rate achieved is 90.0%. K. B. Zende et.al. [4], describe a fake note detection system automatic recognition of Indian currency security feature based on MATLAB system. They are so many step including in this process is feature extraction, image segmentation, edge detection, bit plane slicing and comparison of image. In this paper extract some many feature watermark Detection, Security Thread Detection, checking currency series number, identification mark and sees through register. Here, they propose a GUI platform to check the currency is fake or real. Li Liu et al. [5], introduce an approach to detect fake coins using digital images. In this paper, represented in the dissimilarity space, which is a vector space constructed by comparing the image with a set of prototypes. To recognized key points they used DOG and SIFT detector.

4. Proposed System

The proposed system is using image processing to detect the currency. The input is a photographed or scanned image that is given to the system which can be of .png and the output tells whether the currency is genuine or not. The process contains techniques such as image pre-processing, grey scale conversion, edge detection, segmentation, feature extraction and comparison of feature. Figure 1 shows the architecture diagram that is for

the proposed system.

Fig. 1 Architecture diagram of proposed System The proposed algorithm is presented as follows

  1. Image of note will be taken by web camera.
  2. The taken image is RGB image and then further it will be converted into gray scale.
  3. Edge detection will be performed on the whole gray scale image.
  4. After detecting edges, the four parameters of the note will be cropped and segmented
    1. After segmentation, the parameters of the note will be extracted.
    2. The parameters of suspected image are compared with the standard pre-stored image in the system.
  5. If it matches then the note is real one otherwise it is fake.

detecting sharp changes in image brightness is to capture important events and changes in properties of the world. Edge detection helps to detect all the edges of the necessary ROI to perform various operations in the latter stages.

  1. Segmentation : Image segmentation is the process of dividing an image into multiple parts. This is typically used to identify objects or other relevant information in digital images. shows a few examples of the techniques that can be used to perform segmentation.
  2. Feature Extraction : Feature extraction is a type of dimensionality reduction that efficiently represents interesting parts of an image as a compact feature vector. This approach is useful when image sizes are large and a reduced feature representation is required to quickly complete tasks such as image matching and retrieval. The features are extracted and then used for comparison in the further step.
  3. Comparison : The features that are extracted from the previous step are used for comparing with the stored features and then the results are displayed as to the currency being genuine or fake. Finding Correlation : For finding Correlation of two images we have to follow this steps:
  1. Load two images and extract their pixel-by- pixel information
  2. Normalize and down sample the pixel information
  3. Calculate cross-correlation using the processed pixel information
    1. Generate visual summaries of cross- correlation, highlighting areas of maximum image overlap.

6. Conclusion

Currency use is a necessity for survival and hence it is always necessary to keep in track of its originality. Paper currencies are used much more in Bangladesh and hence a system to detect the fake currency is needed. As the new currencies are used in the market, the proposed system seems to be useful to detect the currency to be genuine or not. This system compares more features for feature extraction than other proposed systems. It also shows where the differences are in the currencies instead of simply displaying the result. Restriction:  This project cannot be able to detect the currencies whether it is fake or not, of other countries except Bangladesh.  This project is only able to detect the currencies whether it is fake or not with denomination 1000 of Bangladeshi currency. Future Scope  This project cannot be able to detect the currencies of other countries except Bangladesh. So in the future we can make this project possible to detect the currencies of other countries also.  This project is only able to detect the currencies whether it is fake or not with denomination 1000 of Bangladeshi notes. So in the future we can make it possible that it will detect the currencies with all denomination.  In this project, we worked using a few features of the currencies. So in the future we can be able to work with all features of currencies to increase the accuracy of the project.

References

[1] P. D. Deshpande and A. Shrivastava,“ Indian Currency Recognition and Authentication using Image Processing ,” IJARSE, Vol. 07, No. 7, pp. 1107-1119, 2018. [2] Y. Neeraja, B. Divija and M. Nithish Kumar, “Fake Currency Detection Using K-nn Technique,” IJREITSS, Vol. 09, No. 1, pp. 201-205, 2019. [3] K.Sawant and C. More, “Currency Recognition Using Image Processing and Minimum Distance Classifier Technique,” IJAERS, Vol. 3, No. 3, pp. 1-8, 2016. [4] K. B. Zende, B. Kokare, S. Pise and P. S. Togrikar, “Fake Note Detection System,” IJIRT, Vol. 4, No. 1, pp. 46 - 49, 2017. [5] Li Liu and Yue Lu, “An Image-Based Approach to Detection of Fake Coins,” TIS, June 2017. [6] Devid Kumar, Surendra Chauhan,”Indian Fake Currency Detection Using Computer Vision” Volume: 07 Issue: 05 | May 2020 [7] Munshi Md. Alimushwan ,Akiful Mohaimin ,Rifat Islam , Shahriar Chowdhury “Fake Currency Detection using Image Processing Method”.