CURRENCY VALIDATION

SYSTEM USING MOBILE

Currency Currency is the means of purchasing

through trade. Today, currency generally refers to printed or minted money. Sometimes only paper bills are thought of as currency, while other times coins are included. Currency involves the exchange of goods or services for cash.

Currency counterfeit

Counterfeiting of money is one of the oldest crimes in history. It was a serious problem during the 19th century when banks issued their own currency. At the time of the Civil War, it was estimated that one-third of all currency in circulation was counterfeit

Currency counterfeit detectors

Why currency validation system

Because of the availability of mobile in every hand

The customer didn’t have to buy any of the previous devices only he pick his mobile phone up and take a photo for the currency and through our application he can determine whether that currency real or false .

Currencies Our system applied on Egyptian

currencies

System overview

System overview

Used Technologies: Matlab Microsoft visual studio Windows phone developer tools

Processing steps Taking a photo for the suspected currency

via mobile Sending the currency image to the server

to be checked Preprocessing of the input image to

remove noise and background Currency value determinant Extracting special features Checking the validity of the currency Show result and send it back to the mobile

Step1: taking a photo for the suspected currency via mobile

Check to see if the camera is available on the device

if not available Message ===== > The camera not supported on

the device. if available Use standard camera if available. Otherwise, use front-facing camera on the

device. Start image capture Save picture as JPEG to isolated storage.

Step2: Sending the currency image to the server to be checked

In this steps the mobile send the captured image to the server using network

And the mobile waiting for response

send image to server by network Connecting to a TCP Socket Server

create a socket and connect to the server by using the System.Net.Sockets APIs.

Send Request to Server for connect by Host name and Port Number

Server listen to any request and Accept On Connection

Client Convert image to Array of bytes Send Array to server

Waiting for Result from Server Server Received Byte Array Convert array of bytes to Image Run processing Operations on This

Image

Step3: Preprocessing of the input image to remove noise and background This step concerns with preparing the

input image for the processing First, resizing the input image to a �

predefined general size Second, removing the image noise if �

exist finally, removing the currency background

Removing noise

Using blurring filters to remove noise from the image

Removing background

Blobcounter class

Step4: Currency value determinant In this step we determine the value of �

the currency There was 2 methods � 1.MSE

2.comparison method using Surf algorithm

1 -MSE

Create a matlab function that calculate the mean square error for the spectrum of the image

Binding that matlab function with c# Crop a rectangle from the upper left corner� Apply matlab function that calculate MSE �

in the cropped part Test the result and get the range� Determine the currency value�

MSE limitations

By examining the MSE method we find �an error rate between 20% & 40%

That rate come from inference between 200L.E & 100L.E rates

So, we apply the second method .�

Comparison method

In this method the system determine the value of the currency by comparing the input currency with a small database that contains a number of different currencies

and get the similarity rate for each comparison

We determine the currency value by �getting the highest similarity rate in comparison process

Step5: Extracting security features

After determining the value of currency, we need to extract the security features for each currency

Security marks of currencies are those marks with which we can determine whether the currency is true or false

Some important security marks in the Egyptian currency:

Shiny intermittent tape

Magnetic security tape

Eye of Horus

A print using an ink which its color is changeable when tilting the currency

Step6: Checking the validity of the currency

In order to check the validity of the currency we need to compare the extracted security marks with another real currency marks that is saved in the system

This process is done using two different techniques:

1. Neural Network

2. Surf algorithm

Neural network

Simply we use xor neural network but with changing the inputs of the network to the numbers which obtained by counting ones exits in rows and columns of special parts in the currency like Shiny intermittent tape this is called projection.

In the training process we use back propagation algorithm to learn neural by using at least one original currency and one that is not original .

Neural network

The ideal output of the original currency is 1 and the ideal output of the not original one is 0.

The network stopped when the number of epochs is larger than 5000 and the error is less than 0.001.then we test the network by a new data.

We compare the output of the network by a threshold to determine which it is original or not.

Surf algorithm

Convert the input image to integral image

Applying fast Hessian filter for generating interest point

For each interest point generate surf descriptor

Comparison between surf descriptors in each image

Surf descriptors comparison

Step7: Show result and send it back to the mobile In this step the mobile receive the result

from the server and show a message to the user

Limitations Camera with more than 5 MP efficiency The photo of currency must be taken

with black background Our system is not applied in old versions

of currency

Team: Ahmad Mohammed Akl Abdurrahman Mohammed Amira Raft Ahmed Elhmamsy Ibrahim El-Said Mohammed El-Said �

Harhera Mai Magdy Mohammad ElKobrosly Nada Said El-Said Essa Nada Mohammed Mohammed Yousef�

Thank you