Note to Coin converter using Digital Image Processing

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1771
Note to Coin converter using Digital Image Processing
Prof. Madhav Thigale1, Lina Ladhane2, Madhuri Mangutkar3 , Neha Gaikwad4
1Assistant Professor, E&TC Dr. D. Y. Patil Institute of Engg. Management and
Research, Pune, Maharashtra, India
234Student, E&TC, Dr. D. Y. Patil Institute of Engg. Management and Research, Pune, Maharashtra, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Requirement of coins in a day to day transaction
has increased; we have to suffer a lot for the change in various
public places like bus station, railway station, malls, parks,
even in rural areas. So we thought to develop an exchanger
machine which will give us coins instead of notes. As there are
lots of techniques to detect the Indian currency note, we are
using fake note detection and digital image processing. A user
will place the note and then with the help of image processing
the Indian currency note will be identified. We are using
MATLAB algorithm for detection of the value of note and we
have implemented a fake note detection unit using UV LED
and photodiode.
Key Words: DIP, Arduino UNO, Fake note, Indian
currency
1. INTRODUCTION
At present note to coin converter is being used in various
countries including India, but in India such systems are
scarce and very few people know about it and also their
availability is limited to few banks, but not at public places
where the need is more. So our idea is to implement such
system at public places which is smaller,lighter anddoesnot
require supervision.
The main process of the project is to identify which note is
placed in the machine with the help of image processing to
identify and detect if the note is real or fake. If note is real
camera takes picture of it and find’s outitsvalueusingimage
processing technique and then accordingtothevalueitgives
equivalent number of coins.
For detecting the note the MATLAB algorithm runs and the
result is given to the controller which will manipulate the
coin container through relays and motors, the user simply
press the keypad for which type of change hewantswhether
one rupee, two rupee coins or five rupee or mixed andhence
in the output we get coins as user requirement.
2. SYSTEM ARCHITECTURE
2.1 Note placing unit:
The note is placed in exact position in the unit and the web
camera takes the pictureofthecurrencynoteplacedandthen
it is sent to the image processing unit for fake note detection.
The note should not be folded and nothing should be written
on the note.
2.2 Image processing unit:
In image processing various operators are used that are
Robert, Sobel, Prewitt, Canny operators, these are edge
detection methods. Currently Canny edge detector is known
as one of the best edge detectors. Canny edge detector is an
edge detection operator that uses multi stage algorithm to
detect a wide range of edges in images and it requires less
RAM to run on the memory.
2.3 Segmentation Algorithm:
Image segmentation is the process of partitioning a digital
image into set of pixels. Image segmentationistypicallyused
to locate objects and boundaries in images. If the object has
sufficient contrast from the background it can be easily
detected in an image.
The object to be segmented differs in contrast from the
background image. Any changes in the contrast will be
detected by operators that are used to calculate the gradient
of image. The gradient image can be calculated and a
threshold can be applied to create a binary mask containing
the segmented cell.
The threshold method is based on clip level which turns a
grey scale image into binary.
The threshold value only allows 200 to 255 pixel values to
pass behind a black background so that the 0 pixel value
which is black is not passed and all the other whitepixelsare
passed.

2.3 Viola-Jones Algorithm:
This object detection framework is the first object detection
framework to provide as good as object detection rates in
real-time proposed in 2001 by Paul Viola and Michael Jones.
Despite it can be trained to detect a discrepancy of object
classes, it was provoke primarily by the problem of face
detection.
The problem to be solved is detection of faces in an image. A
human can do this easily, but a computer needs precise
instructions and constraints. To make the task more
manageable, Viola–Jones requires full view frontal upright
faces. Thus in order to be detected, the entirefacemustpoint
towards the camera and should not be tilted to either side.
While it seems these constraints could diminish the
algorithm's utility somewhat, because the detection step is
most often followed by a recognition step, in practice these
limits on pose are quite acceptable.
The characteristics of Viola–Jones algorithm whichmakeita
good detection algorithm are:
Robust – very high detection rate (true-positive rate) & very
low false-positive rate always.
Real time – For practical applications at least 2 frames per
second must be processed.
Face detection only (not recognition) - The goal is to
distinguish faces from non-faces(detectionisthefirststep in
the recognition process).
2.4 Coin Dispatching
MATLAB identifies the currency note and assigns a variable
the value of the note. The user enters the number of coins he
wants using keypad. The total amountofchangeiscompared
with the available value and if its accurate the signal is sent
to the microcontroller through the serial port.For eachsetof
coins one motor is used. According to user the selected
number of coins with the respective motorrotatesfora fixed
duration to consign a single coin. Therefore N number of
coins the motor is rotated for N times for a specific duration.
3. Hardware Description
3.1 Arduino Uno
The Arduino Uno is a microcontroller based on the
ATmega328. Which having 14 digital input/output pins out
of which 6 can be used as PWM outputs,6 analog inputs and
a 16 MHz crystal oscillator, a
USB connection, a power jack, a ICSP header, and a reset
button. It contains everythingwhichisneededtosupport the
microcontroller. The Arduino Uno differs from all preceding
boards in that it does not use the FTDI.
3.2 Relay Module
Relay module is an electrically operated switch that allows
to turn on or off a circuit using voltage and/or currentwhich
is much higher than a microcontroller could handle.Thereis
no connection established between the low voltage circuit
operated by the microcontroller and also highpowercircuit.
In this module each channel has three connections named
NC (normally closed), NO (normally open) and COM
(common).
When relay contact is NO, there is an open contact when the
relay is not energized.
When relay contact is NC, there isanclosedcontactwhenthe
relay is not energized.
3.3 DC Motor
A DC motor is a rotatory electrical machine that converts
DC electrical energy to mechanical energy. All type of DC
motors have some internal mechanism which is electro-
mechanical or electronic, to periodically change the
direction of current flow in parts of motor.
The speed of the motor can be controlled over a wide range
by using either a variable supply voltage or by changing
strength of current in its field windings.

3.4 Flow Chart
4. CONCLUSION
We are develop an interactive system that generates
currency recognition system using image processing with
the help of MATLAB. In day to day life we are suffering for
change of currency at many public places, so this system
which is real time application for all real time places i.e. in
the buses, railway station, malls are used.
REFERENCES
[1] A. Bade and D. Aher, “Note to Coin Exchanger Using
Image Processing ,” IJRITCC, vol. 1, Mar. 2013, pp. 154-
158.
[2] Kajal Gawali and S.Patil, “Note To Coin Exchanger with
Fake note Detection”, ICRIEM-16,ISBN:978-81-932074-
5-1, March-2016
[3] Parminder Singh Reel, GopalKrishan, SmartiKotwal,“
Image Processing basedHeuristic AnalysisforEnhanced
Currency Recognition,” Vol 2, No 1 (January 2011)
International Journal of Advancements in Technology
http://ijict.org/ ISSN 0976-4860K.Elissa,“Titleofpaper
if known,” unpublished.
[4] Amol A. Shirsath, S. D. Bharkad, “A Review of Paper
Currency Recognition System”, IOSR Journal of
ComputerEngineering(IOSR-JCE)e-ISSN:2278-0661,p-
ISSN: 2278-8727Volume 10, Issue 1 (Mar. - Apr. 2013),
PP 71-76
[5] www.wikipedia.org

Note to Coin converter using Digital Image Processing

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