fake note detection system - ijirt. · pdf file© june 2017 | ijirt | volume 4 issue 1 |...

© June 2017 | IJIRT | Volume 4 Issue 1 | ISSN: 2349-6002

IJIRT 144578 INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN TECHNOLOGY 46

Fake Note Detection System

Kanchan B.Zende1, Varsharani Kokare2, Sunetra Pise3 and P. S. Togrikar4

1, 2, 3 Student, Electronics and Telecommunication, S.B.Patil College of Engineering Vangali, Indapur,

Maharashtra, India 4Assistant Professor, Electronics and Telecommunication, S.B.Patil College of Engineering Vangali,

Indapur, Maharashtra, India

Abstract—It is the major problem for everyone. India is

a developing country, Production and printing of Fake

notes of Rs.100 are degrading economic growth of our

country.In this present scenario, we are designing a

MATLAB based system which identifies Fake note from

the genuine one. For this purpose here we are using

MATLAB software . . The characteristics extraction is

performed on the image of the currency and it is

compared with the characteristics of the genuine

currency. The currency will be verified by using image

processing techniques. The approach consists of a

number of components including image processing, edge

detection, image segmentation and characteristic

extraction and comparing images. The desired results

shall verify with MATLAB soft-ware.

Index Terms—Currency, camera, software detector

I. INTRODUCTION

Fake note detection system is developed for

recognizing fake note from the genuine. The only

solution that is presently available for common man to

detect counterfeit currency is Fake Note Detector

Machine. This machine is mostly available only in

banks which is not reachable every time by average

citizen. . All these scenarios need a kind of solution for

common people to judge a forged bank note and to

refrain our currency from losing its value. MATLAB

is the computational tool of choice for research,

development and analysis. The image formats

supported by MATLAB are JPEG, PCX, TIFF, PNG

etc. Characteristic extraction of images is challenging

work in digital image processing. It involves

extraction of visible and some invisible features of

Indian currency notes. A good characteristic extraction

scheme should maintain and enhance those

characteristics of the input data which make distinct

pattern classes separate from each other.

1.1 Problem Statement

Counterfeit notes are one of the most biggest problem

occurring in cash transactions. For country like India,it

is become big hurdle .Because of the advances in

printing ,scanning technologies it is easily possible for

a person to print fake notes with use of latest hardware

tools

1.2 Literature Survey

[1] - Indian is a developing country, Production and

printing of Fake .In this article, recognition of paper

currency with the help of digital image processing

techniques is described. Around eight characteristics

of Indian paper currency is selected for counterfeit

detection. The identification marks, optical variable

link, see through register and currency color code

decides the currency recognition. The security threads,

water mark, Latent image and micro-lettering features

are used for currency verification. The characteristics

extraction is performed on the image of the currency

and it is compared with the characteristics of the

genuine currency.

[2] The expansion of modern banking services

necessitates the needs for automatic currency

recognition and authentication system, thus

encouraging many researchers to develop high

accuracy, reliable and high processing speed

techniques. To detect the authenticity of currency note

there are two methods i.e. first line inspection method

and second line inspection method. First line

inspection method includes varied density

watermarks, ultraviolet fluorescence, intaglio printing,

micro text and hologram while the second line

inspection methods include isocheck/ isogram, fiber

based certificates of authenticity, color and feature

analysis.



[3] The currency notes are provided with few special

identification marks only for the blind people so that

they may easily recognize the denomination correctly.

Every currency note has its denomination engraved at

the top right end which is sensitive to touch, but this

mark fades away after the currency note goes in

circulation for some time. This impaired people to

correctly determine the denomination of the currency

note.

A currency recognition system for visually impaired

has been developed in this paper. It uses a currency

localization technique to extract the currency note

from a color image. The technique requires feature

based currency note localization. This is applied using

the Image Processing toolbox available in Mat lab.

[4] Money is an integral part of our needs so its

genuinely is important. Circulation of fake money can

disturb the economic growth process of our country.

Circulation of fake money causes much inconvenience

to people. Many people are still not aware of how to

detect fake notes and the measures which are to be

taken into consideration. In this paper we are focusing

on an advanced mobile based application that is used

to identify fake money. Application of Counterfeit is

to empower the common man with an easily available

device to help him detect fake notes. This application

can be used on day-to-day basis by us for identifying

fraudulent currency notes then and there. Unlike

existing money detectors in banks, Counterfeit:

Currency Detector will provide user friendly and

portable application to find forged banknotes.

II. BLOCK DIAGRAM

Fig.1: System Block diagram

Description

This application is user-friendly and can be used on

day-to-day basis. For using this application, user need

to take a photograph of the required note holding it

against sufficient light. This light could be any light

like sunrays, tube light or bulb which helps the camera

of mobile phone to detect the different features of the

note. Then the software examines the note and gives

the appropriate result to the user about the authenticity

of the note.

2.1Currency:-

Money is an integral part of our needs so its genulity

is important. Circulation of fake money can disturb the

economic growth process of our country. Circulation

of fake money causes much inconvenience to people.

Many people are still not aware of how to detect fake

notes and the measures which are to be consideration.

just needs to take an image of the note with help of

camera.

Specification:-

Value- 100 rs

Width- 157 mm

Height- 73mm

Design-mahatma Gandhi

2.2Camera:-

User need to take a photograph of the required note

holding it against sufficient light. This light could be

any light like sunrays, tube light or bulb which helps

the camera of mobile phone.

Specification:-

Megapixels-8megapixles rear camera with LED flash

Resolution-1280x768 pixels

2.3Currency detector software:-

This application has mainly Watermark Detection,

Security Thread Detection, checking currency series

number, identification mark and sees through register

mechanism which actually detects the trueness of the

currency. The GUI of this application is user-friendly

to check the currency. User is completely unaware of

the complexity of counterfeit currency. Finally the

currency detector software provides the result to the

user of the required currency based on the comparison

done between the details of genuine note stored in the

database and the tested note.

Specification-

Get base amount-convert an amount in current display

currency to base currency (US$).



Get currencies()- return all currencies supported by

this server.

Get currency (string)-Get currency for specified ISO

mode.

Get display amount()-convert a base amount to current

display currency.

All this description can be design in flow of operation.

Fig -3: Flow of Operation

Result

Fake Note

Real note:

III. CONCLUSIONS

Detecting the fraud notes is need of common man

today. Henceforth, common people would not require

running to banks for checking a note. Also this is a

step towards reducing issues like inflation which

occurs due to Counterfeit currencies. This is a

MATLAB based system for automatic recognition of

security features of Indian currency. The low cost

system, using effective and efficient image

processing techniques and algorithms, provide

accurate and reliable results at good throughput as

shown by experimental results. The developed

algorithm works for Indian denomination 100.

Input Image

Image Preprosessing

Image Resize

Image Segmentation

(Feature cropping)

() Feature Extraction

Feature

Comparis

on With

Database

Database

Result



REFERENCES

[1] Hassanpour,H., Yaseri, A. and Ardeshir G.:

“Feature extraction for paper currency

Recognition” In International Symposium on

Signal Processing and its Application (ISSPA)

Sharjah,

[2] R.C.Gonz alez and R.E.Woods, Digital Image

Processing,2nd ed.,Prentie Hall,2002

B.Manjunath and W.Ma,”texture features for

browsing and retrieval of image data,”IEEE

Trans.Pattern Anal

[3] Kuldeep Verma, et al.,”Indian Currency

Recognition Based On Texture Analysis”,

Institute of Technology, Nirma University,

Ahmedabad – 382481, 08-10 December, 2011

[4] Mriganka Gogoi, et al.,”Automatic Indian

Currency Denomination Recognition System

based onArtificial Neural Network”, 978-1-

4799-5991-4/15©2015 IEEE

[5] Suriya Singh, Shushman Choudhury, Kumar

Vishal and C.V. Jawahar,“Currency

Recognition on Mobile Phones”

[6] Megha Gupta, et al.,” Classification

Techniques Analysis”, Csio Chandigarh, India,

19-20 March2010

Biographies

[1] Miss. Kanchan Bhimrao Zende– Student,

Department of Electronic and

Telecommunication, S.B Patil, College of

Engineering ,Indapur, Maharashtra.

[2] Miss. Varsharani Kokare– Student,

Department of Electronics and

telecommunication, S.B. Patil, College of

Engineering, Indapur, Maharashtra.

[3] Prof. P.S.Togrikar-Faculty, Department of

Electronics and telecommunication, S.B. Patil,

College Of Engineering, Indapur, Maharashtra.

fake note detection system - ijirt. · pdf file© june 2017 | ijirt | volume 4 issue 1 |...

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