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Tags: Currency converter Impact of currency converter Evaluation of currency converter Assessment of currency converter Design and implementation of currency converter




There are around 200+ different currencies used in different countries around the world. Conversion from one currency to another is a very important endeavor especially when it comes to marketing and travel. Currency conversion system is implemented to reduce human power to automatically recognize the amount monetary value of currency and convert it into the other currencies without human supervision. The software interface that we are proposing here could be used for various currencies (we are using four in our project).

Many a times, the stress and brain work required for manual currency conversion is much. Sometimes currency notes are blurry or damaged; many of them have complex designs to enhance security. This makes the task of currency recognition very difficult. So, it becomes very important to select the right features and proper algorithm for this purpose. The basic requirements for an algorithm to be considered as practically implementable are simplicity, less complexity, high speed and efficiency. Our main aim is to design an easy but efficient algorithm that would be useful for maximum number of currencies, because all currencies have different security features, making it a tough job to design one algorithm that could be used for recognition of all available currencies. Writing different programs for all is also a tedious job. This project will be designed using PHP programming language for the front-end and MySQL for the back-end.



1.1 Background of the Study

The staffs who work at places like money exchange offices have to distinguish between different types of currencies and convert them to other currencies and that is not an easy job. They have to remember the symbol of each currency. This may result into wrong recognition, so they need an efficient and foolproof system to aid in their work. The aim of our system is to help people who need to recognize different currencies, and be able to convert them to another currency using a known exchange rate. With development of modern banking services, automatic methods for paper currency recognition become important in many applications such as vending machines. It is very difficult to count different denomination notes in a bunch. This project proposes an image processing technique for paper currency recognition and conversion. The extracted region of interest (ROI) can be used with Pattern Recognition and Neural Networks matching technique. Image Processing involves changing the nature of an image in order to improve its pictorial information for human interpretation. There are various techniques for currency recognition that involve texture, pattern or color based. We use digital image processing techniques to find region of interest, after that Neural Network and Pattern Recognition Technique is used for matching the pattern. A number of methods for banknote classification have been proposed. Template matching is often used as a simple method to classify banknotes.
However, new template or matching rules are required for new bill types. An effective way to overcome the problem is to extract features from bill images representing unique characteristics of bill data. After studying different currencies and considering the availability, we have chosen 5 currencies to work on
for this project. The chosen currencies are Indian Rupees (INR), Australian Dollar (AUD), Euro (EUR), Nigerian Naira (NGN) and US Dollar (USD).

A lot of work has been done in order to recognize currencies automatically,
A distinctive point extraction method used a coordinate data extraction method from specific parts of a Euro banknote representing the same color. In order to recognize banknotes, they used two key properties of banknotes: direction (front, rotated front, back, and rotated back) and face value, neural network-based bill recognition and verification method, the learning vector quantization (LVQ) method to recognize Italian Liras, 4 Robust and Effective Component-based method for Banknote Recognition by SURF Features. [Rubeena Mirza, 2012].

In another research work, a simple statistical test is used as the verification step, where univariate Gaussian distribution is employed, in another technique for paper currency recognition, three characteristics of paper currencies including
size, color and texture are used in the recognition. [Vipin Kumar Jain, 2013] After studying the previously used methods for currency recognition, we can see that most of these methods/algorithms use Artificial Neural Networks.

1.2 Statement of the Problem

Currently, human is needed to recognize the amount of the currency and to convert it manually. This is stressful especially to people who aren’t so smart in calculations. So, this project is developed to replace human power to recognize the amount of the currency.

Currency Recognition and converter system is implemented to reduce human
power to automatically recognize the amount of currency and convert it into the other currency without human supervision.

1.3 Objectives of the Study

The main objective of the study is to develop a currency converter for major countries in the world. The countries to be used here are Indian Rupees (INR), Australian Dollar (AUD), Euro (EUR), Nigerian Naira (NGN) and US Dollar (USD). To achieve this objective, specific objectives are laid out which include:

i. Develop a system which able to convert between the currencies mentioned above

ii. A system in which an exchange rate for any particular currency can be stored and used in conversion between the correspondent currency.

iii. Develop the program that can determined the amount of paper currency
using neural network

iv. Extract the data from the currency image by using digital image processing toolbox.

1.4 Scope of the Study

The scope of this project is to develop a currency recognition and converter
system by using image processing and neural network. In other to implement this system we have to use MATLAB Toolbox to achieve the objectives of the project.

The system will be able to recognize the currency amount, integrate hardware and software, extract the data from the currency image by using digital image processing toolbox, accept and store an exchange rate for conversion between currencies.

1.5 Significance of the Study

This study will be useful to every organization that deals with money, it will help in easy conversion of money to another. It will be of immense help to bureau de change as it will ease the task of currency recognition and conversion. This work is also significant to scholars who needs to make research about currency recognition and conversion.

1.6 Limitations of the Study

The major limitation of this thesis is during the actual software development. The source code for image recognition was difficult to obtain as Php programming language don’t have much support for image recognition.

Also due to lack of enough money, time and confidentiality of information, system developed convers all aspect of money conversion and few aspects of currency recognition.

1.7 Definition of Terms

Currency: Money or any item used for exchange of goods and services and facilitates transactions

Conversion: The act of bringing out an equivalent of one commodity in another commodity

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