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1.1       Background of the Study

A biometric system is essentially a pattern recognition system that operates by acquiring biometric data from an individual, extracting a feature vector from the acquired data, comparing this feature vector from the database feature vector. Person authentication has always been an attractive goal in computer vision. Authentication systems based on human characteristics such as face, finger, iris and voice are known Biometrics systems. The basis of every biometric system is to get the input image and generate prominent feature vectors like color, texture, etc.

Today, biometric recognition is a common and reliable way to authenticate the identity of a living person based on physiological or behavioral characteristics. A physiological characteristic is relatively stable physical characteristics, such as fingerprint, iris pattern, facial feature, hand silhouette, etc. This kind of measurement is basically unchanging and unalterable without significant duress. A behavioral characteristic is more a reflection of an individual’s psychological makeup as signature, speech pattern, or how one types at a keyboard.

The degree of intra-personal variation in a physical characteristic is smaller than a behavioral characteristic. For examples, a signature is influenced by both controllable actions and less psychological factors, and speech pattern is influenced by current emotional state, whereas fingerprint template is independent. Nevertheless all physiology-based biometrics don’t offer satisfactory recognition rates (false acceptance and/or false reject rates, respectively referenced as FAR and FRR). The automated personal identity authentication systems based on iris recognition are reputed to be the most reliable we consider that the probability of finding two people with identical iris pattern is almost zero. That’s why iris recognition technology is becoming an important biometric solution for people identification in access control as networked access to computer application. Compared to fingerprint, iris is protected from the external environment behind the cornea and the eyelid. No subject to deleterious effects of aging, the small-scale radial features of the iris remain stable and fixed from about one year of age throughout life.

1.2       Statement of the Problem

In recent years, in line with global trends, the banking sector has faced rising levels of cash card fraud resulting in the subsequent illegal withdrawal of funds from customer accounts. The account-holder is normally held responsible for the loss of funds from their accounts and, as such, the impact of this fraud could be potentially far-reaching.  As a result of this, the banking sector has to embrace biometrics as the solution to the growing problem of counterfeit ATM cards and ID theft. Among others include

1.      Fraudulent card readers, called skimmers are placed over the authentic reader to transfer numbers and codes to nearby thieves.

2.      Spy cameras are also used by password voyeurs to collect access codes.

3.      In cases of card lost, if the loss is not noticed immediately, consumers may loose all funds in an account.

4.      If you forget your pin number, you cannot use the card.

5.      The machine can retain your card when the machine malfunctions, when you forget your secret number or if the card is damaged.

1.3       Aim and Objectives

The aim of this project work is to simulate an embedded fingerprint authentication system, which is used for ATM security applications. The specific objectives include:

       I.            To provide a platform that will allow the bankers to collect customers’ finger print.

    II.            To provide a platform that will allow the bankers to collect customers’ phone number and store them in a centralized database.

 III.            To build a system that will forward 4-digit number to the customers’ mobile phone when the finger print reading matches.

 IV.            To provide a platform that allows the customer to run his transaction after the system accepts the code generated.

    V.            To create a platform that will be able to analyze biometric data in the global image analysis.

1.4       Scope of the Study

This study is on implementing ATM security using the finger print. There is a centralized database to take care of customers’ personal and biometric data. The system is designed to query the database by inputting a user finger print and if it matches with the one in a system it will generate a 4-digit number that will enable the user to continue with his transactions.

1.5       Significance of the Study

The current system of passwords and pin numbers needed to access financial services has drawn a lot of criticism of late due to the increasing incidents of hacking. The system is at the mercy of hackers, who use the hacked data to draw funds from the victims account. This is where Biometrics with its foolproof system comes in. Some of the reasons for building this system include:

vIncrease security - Provide a convenient and low-cost additional tier of security.

vReduce fraud by employing hard-to-forge technologies and materials. For e.g. minimize the opportunity for ATM fraud.

vEliminate problems caused by lost ATMs or forgotten passwords by using physiological attributes. For e.g. prevent unauthorized use of lost, stolen or "borrowed" ATM cards.

v Replace hard-to-remember secret digits which may be shared or observed.

vIntegrate a wide range of biometric solutions and technologies, customer applications and databases into a robust and scalable control solution for facility and network access

vMake it possible, automatically, to know WHO did WHAT, WHERE and WHEN!

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