Research Article
a
May
2019
Computer Science and Software Engineering
ISSN: 2277-128X (Volume-9, Issue-5)
Effective Method of Fake Currency Detection System using
Image Processing
Hlaing Htake Khaung Tin
Faculty of Information Science,
University of Computer Studies, Yangon, Myanmar
Abstract— This study will provide information about the different methods and algorithms used for fake currency detection system. The fake currency detection system is developed to detect the fake currency by applying different techniques and methods on currency note. Fake currency can be found only in high denominations like 10,000 kyats and 5,000 kyats in Myanmar. The increasing technological advancements have made the possibility for creating more counterfeit currency which is circulated in the market which reduces the overall economy of the country. This system consists of many steps like input image, preprocessing, and feature extraction, comparison and output image. There are various ways to acquire image such as with the help of camera or scanner. Acquired image should retain all the features.Acquisition of image is process of creating digital images, from a physical scene. Here, the image is captured by a simple digital camera such that all the features are highlighted. Image is then stored for preprocessing. After preprocessing apply the image segmentation and features extraction. Finally compare the image into original image and then output the image. The result will predict whether the currency note is fake or not.
Keywords— fake; currency; detection; feature extraction; myanmar kyats.
I. INTRODUCTION
Over the past few years, as a result of the great technological advances in colour printing, duplicating and scanning, counterfeiting problems have become more and more serious. Fake currency detection system can be used in places such as shops, banks counter and automated teller machine, auto seller machines etc.[1]
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 find it feasible to buy machines that use UV light and other techniques to detect the authenticity of the currency. But for common people it is very difficult to just detect whether the currency is fake or genuine and they may face losses especially during bank deposits or transactions. This system is designed such that any person can use it easily and detect the authenticity of the currency he has by using the visual features of the currency [5].
An image may be defined as a two-dimensional function, f(x, y), where x and y are (plane) coordinates and the amplitude of f at any pair of coordinates (x, y) is called the intensity values of f are all finite, discrete quantities, we call the image a digital image. The field of digital image processing refers to processing digital images by means of digital computer. Note that a digital image is composed of a finite number of elements each of which has a particular location and value. These elements are called picture elements, image elements and pixels [9].
Under section 8(a) of the Central Bank of Myanmar Law, The Central Bank of Myanmar is acting as the sole issuer of domestic currency, either bank notes or coins. As the monetary authority its the central Bank of Myanmar formulate and implements monetary policy, with the aim to preserve the value of the Myanmar currency and to promote efficient payments mechanisms. After the State Laws and Order Restoration Council took power in 1988, the Central Bank of Myanmar issued Lion series and Aung San series was replaced by gradually. Denominations are 1,5,10,20,50,100,200,500 and 1000 kyats notes and 1,5,10,50 and 100 kyats coins. The color of the 1 kyat coin is bronze color, the 5 and 10 kyats coins are golden yellow color and the 50 and 100 kyats coins are silver color respectively on 1st October 2009 Central Bank of Myanmar issued new currency notes of 5000 kyats to easier handling for the people. And new currency notes of 10000 kyats issued to the public effect from 15th June 2012.[6]
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 44-48 distinguish easily between genuine and counterfeit notes if they look at them thoroughly. But the volume of counterfeit notes is very small compared to currency in circulation therefore is negligible and hence there is no major problem in Myanmar on occurrence of counterfeits. [6]
A Fake currency detection using image processing and other standard methods by using various methods like watermarking, optically variable ink, florescence, security thread, intaglio printing, latent image, micro lettering and identification mark. By combining two various components of two images then, the variation will be decreased. But by using layman method the fake note is detected [10].
The system is based on Image processing where a number of steps are used to process the image of a currency and give the result to the user that the currency is genuine or not.
The research paper mentions the following details. In section II, there are brief information on some related papers that are used for reviewing. In section III, the methodology is mentioned which specifies the different steps used in the entire process of currency detection and the details of the proposed system are mentioned. Section IV shows the conclusions.
II. LITERATURE SURVEY
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. 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 is 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 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 gray scale conversion, edge detection, segmentation, etc. which are performed using suitable methods [4].
The fake currency detection system is developed to detect the fake currency by applying different techniques and methods on currency note. The fake currency detection system should be able to recognize the note quickly and correctly. The fake currency detection system should be able to recognize currency note from any side. Currency recognition system can be used in places such as shops, banks counter and automated teller machine, auto seller machines etc [2].
The techniques for detecting fake currency methods based on bit rate reduction techniques. This article introduces a new approach using cost-saving techniques to extract the most important data from the images of fake bills by applying edge detection algorithms. The proposed technique is in the original image distribution, with the gray gradient 256 in its binary image equal 8. This is useful when analyzing the importance of attributes defined by each image of the original image. Higher-bit bits are evaluated for the blue dollar bill image by applying the Canny Edge Finder algorithm. Then the result is compared to real money and other available techniques that are used to detect fake notes [3].
Automated detecting fake currency system can be very help full to banking or other business so many author work on this technology as per his opinion fake currency detection is very important task in human life. India is also one of them. In this article, recognition of paper currency with the help of digital image processing techniques is described. Six characteristics of Indian paper currency are selected for counterfeit detection included identification mark, security thread, watermark, numeral watermark, floral design and micro-lettering. The characteristic feature extraction is performed on the image of the currency and it is compared with the characteristic features of the genuine currency. The decision making is done by calculating the black pixels. This article is aimed to design a low cost system and quick decision making system [8].
III. METHODOLOGY OF THE PROPOSED WORKS
This research paper proposed the fake currency detection system using image processing techniques for Myanmar Kyats.
A. Flow of Fake Currency Detection Technique
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 44-48
Figure 1. General flow of fake currency detection system
B. Input Image
The image of the currency that has to be checked or verified as a genuine currency is taken as an input for the system. The input image can be acquired using techniques like scanning the image or clicking a picture with the phone and then uploading it to the system.
C. Pre processing
In pre processing step, conversion of a color image to a gray scale image requires more knowledge about the color image. A pixel color in an image is a combination of three colors Red, Green, and Blue (RGB).Similarly, A Gray scale image can be viewed as a single layered image. Different techniques can be used to convert a colour image to gray scale image. [11] 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.
D. 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[4].
E. 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.
F. Features of 5,000 kyats
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 44-48
Figure 2. Features of 5,000 [7]
G. Features of 10,000 kyats
On 9 June 2012, the Central Bank announced that 10,000-kyats notes would be introduced into circulation to better facilitate financial transactions in a largely cash-oriented economy. They were issued on 15 June 2012.
Figure 3. Features of 10,000 [7]
H. Features Description of 5,000 kyats and 10,000 kyats
The flowing table 1 shows the description of 5,000 kyats and 10,000 kyats.
Table 1. Features Description of 5,000 kyats and 10,000 kyats
IV. CONCLUSIONS
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 44-48 ACKNOWLEDGMENT
I would like to express my heartfelt gratitude towards my family and my colleagues who motivated me to work on this research.
REFERENCES
[1] Megha Thakur, Amrit Kaur, "Various Fake Currency Detection Techniques", International Journal for Technological Research in Engineering, Volume 1, issue 11, July-2014.
[2] Ahmed Ali Abbasi, A Review on Different Currency Recognition System for Bangladesh India China and Euro
Currency, Research Journal of Applied Sciences, Engineering and Technology 7(8): 1689-1690, 2014.
[3] Mohammad H Alshayeji, Mohammad Al-Rousan and Dunya T. Hassoun, Detection Method for Counterfeit
Currency Based on Bit-Plane Slicing Technique, International Journal of Multimedia and Ubiquitous, Engineering Vol.10, No.11 (2015)
[4] Vidhi Roy1; Gangey Mishra2; Rahul Mannadiar3; Sushant Patil4, "Fake Currency Detection using Image Processing", International Journal of Computer Science and Mobile Computing, Volume 8, issue 4, April 2019.
[5] Trupti Pathrabe G and Swapnili Karmore 2011 Int. J. CompTrends Tech 152-156
[6] https://www.cbm.gov.mm/content/history-bank-notes
[7] https://en.wikipedia.org/wiki/Burmese_kyat#cite_note-18
[8] B.Sai Prasanthi , D.Rajesh Setty, “Indian Paper Currency Authentication System- A Quick Authentication System” International Journal of Scientific & Engineering Research, Volume 6, Issue 9, September-2015
[9] Ms. Khatke Rasika Nandakumar, Mr. Hindurao Dinkar Gore, "Fake Currency Detector", International Journal
of Advanced Research in Computer and Communication Engineering, Volume 5, Issue 8, August 2016.
[10] D. Alekhya, G. DeviSuryaPrabha and G. Venkata Durga Rao, Fake Currency Detection Using Image Processing
andOther Standard Methods, International Journal of Research in Computer and Communication Technology, Vol 3, Issue 1, January- 2014
[11] Pramod Kaler, ―Study of Grayscale image in Image processing‖ International Journal on Recent and Innovation
Trends in Computing and Communication, ISSN: 2321-8169, Volume: 4 Issue: 11
