The Design And Construction Of A Fingerprint Authentication System (PDF/DOC)
ABSTRACT
Bio metrics technology is rapidly progressing and offers attractive opportunities. In recent years, bio metric authentication has grown in popularity as a means of personal identification in access authentication systems. The prominent bio metric methods that may be used for authentication include fingerprint, palm print, hand print, face recognition, speech recognition, dental and eye bio metrics. In this paper, a microcontroller based prototype access system using fingerprint sensor module is implemented. An 8-bit PIC16F877A microcontroller developed by Microchip Technology is used in the system. The necessary software is written in Embedded ‘C’ and the system is tested.
TABLE OF CONTENTS
TITLE PAGE
APPROVAL PAGE
DEDICATION
ACKNOWELDGEMENT
ABSTRCT
TABLE OF CONTENT
CHAPTER ONE
- INTRODUCTION
- BACKGROUND OF THE PROJECT
- AIM/OBJECTIVE OF THE PROJECT
- SIGNIFICANCE OF THE PROJECT
- SCOPE OF THE PROJECT
- ADVANTAGES AND LIMITATION OF THE PROJECT
- APPLICATION OF THE PROJECT
- PROJECT ORGANISATION
CHAPTER TWO
LITERATURE REVIEW
2.1 REVIEW OF THE STUDY
2.2 OVERVIEW OF BIOMETRICS
2.3 BIOMETRIC FUNCTIONALITY
2.4 REVIEW OF FINGER PRINT
2.5 THE HISTORICAL BACKGROUND OF FINGERPRINTS
2.6 FINGERPRINT RECOGNITION
2.7 PATTERNS OF FINGERPRINT
2.8 HISTORICAL BACKGROUND OF BIO METRIC
CHAPTER THREE
3.0 CONSTRUCTION METHODOLOGY
3.1 BLOCK DIAGRAM OF THE SYSTEM
3.2 DESCRIPTION OF SYSTEM BLOCK DIAGRAM
3.3 CIRCUIT DIAGRAM
3.3 CIRCUIT DESCRIPTION
3.4 SYSTEM OPERATION
3.5 COMPONENTS LIST
3.6 POWER SUPPLY UNIT
3.7 POWER SUPPLY CIRCUIT DESCRIPTION
3.7 DESCRIPTION OF MAJOR COMPONENTS USED
CHAPTER FOUR
4.0 RESULT ANALYSIS
4.1 CONSTRUCTION PROCEDURE AND TESTING
4.2 ASSEMBLING OF SECTIONS
4.3 CONSRUCTION OF THE CASING
4.4 PRECAUSION
4.5 ECONOMIC OF THE PROJECT
4.5 PROJECT VIABILITY
4.6 PROJECT RELIABILITY
4.7 PROJECT MAINTAINABILITY
4.8 PROJECT EVALUATION
4.9 TESTING, TROUBLESHOOTING AND REMEDY
CHAPTER FIVE
- CONCLUSIONS
- RECOMMENDATION
5.3 REFERENCES
CHAPTER ONE
- INTRODUCTION
Biometrics are automated methods of recognizing a person based on a physiological or behavioral characteristic. Biometric-based solutions are able to provide for confidential financial transactions and personal
data privacy. The various features used are face, fingerprints, hand geometry, handwriting, iris, retina, vein and
voice [1]. Fingerprinting or finger-scanning technologies are the oldest of the biometric sciences and utilize
distinctive features of the fingerprint to identify or verify the identity of individuals. Finger-scan technology is
the most commonly deployed biometric technology, used in a broad range of physical access and logical access applications. All fingerprints have unique characteristics and patterns. A normal fingerprint pattern is made up
of lines and spaces. These lines are called ridges while the spaces between the ridges are called valleys. It is
through the pattern of these ridges and valleys that a unique fingerprint is matched for verification and authorization. These unique fingerprint traits are termed “minutiae” and comparisons are made based on these
traits [2]. On average, a typical live scan produces 40 “minutiae”. The Federal Bureau of Investigation (FBI) has reported that no more than 8 common minutiae can be shared by two individuals.
There are five stages involved in finger-scan verification and identification. Fingerprint (FP) image acquisition, image processing, and location of distinctive characteristics, template creation and template matching [3]. A scanner takes a mathematical snapshot of a user’s unique biological traits. This snapshot is saved in a fingerprint database as a minutiae file. The first challenge facing a finger-scanning system is to acquire high-quality image of a fingerprint. The standard for forensic-quality finger printing is images of 500 dots per inch (DPI). Image acquisition can be a major challenge for finger-scan developers, since the quality of print differs from person to person and from finger to finger. Some populations are more likely than others to have faint or difficult-to-acquire fingerprints, whether due to wear or tear or physiological traits. Taking an image in the cold weather also can have an affect. Oils in the finger help produce a better print. In cold weather, these oils naturally dry up. Pressing harder on the platen (the surface on which the finger is placed, also known
as a scanner) can help in this case. Image processing is the process of converting the finger image into a usable format. This results in a series of thick black ridges (the raised part of the fingerprint) contrasted to white valleys. At this stage, image features are detected and enhanced for verification against the stored minutia file. Image enhancement is used to reduce any distortion of the fingerprint caused by dirt, cuts, scars, sweat and dry skin [3]. The next stage in the fingerprint process is to locate distinctive characteristics. There is a good deal of information on the average fingerprint and this information tends to remain stable throughout one’s life. Fingerprint ridges and valleys form distinctive patterns, such as swirls, loops, and arches. Most fingerprints have a core, a central point around which swirls, loops, or arches are curved. These ridges and valleys are characterized by irregularities known as minutiae, the distinctive feature upon which finger-scanning technologies are based. Many types of minutiae
exits, a common one being ridge endings and bifurcation, which is the point at which one ridge divides into two.
A typical finger-scan may produce between 15 and 20 minutiae. A template is then created. This is accomplished by mapping minutiae and filtering out distortions and false minutiae. For example, anomalies
caused by scars, sweat, or dirt can appear as minutiae. False minutiae must be filtered out before a template is created and is supported differently with vendor specific proprietary algorithms. The tricky part is comparing an
enrollment template to a verification template. Positions of a minutia point may change by a few pixels, some minutiae will differ from the enrollment template, and false minutiae may be seen as real. Many finger-scan
systems use a smaller portion of the scanned image for matching purposes. One benefit of reducing the comparison area is that there is less chance of false minutiae information, which would confuse the matching
process and create errors.
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
- Fraudulent card readers, called skimmers are placed over the authentic reader to transfer numbers and codes to nearby thieves.
- Spy cameras are also used by password voyeurs to collect access codes.
- In cases of card lost, if the loss is not noticed immediately, consumers may loose all funds in an account.
- If you forget your pin number, you cannot use the card.
- 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 access security applications. The specific objectives include:
- To provide a platform that will allow the bankers to collect customers’ finger print.
- 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.
- To provide a platform that allows the customer to run his transaction after the system accepts the code generated.
- 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 security system 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:
- Increase security – Provide a convenient and low-cost additional tier of security.
- Reduce fraud by employing hard-to-forge technologies and materials.
- Eliminate problems caused by lost or forgotten passwords by using physiological attributes.
- Replace hard-to-remember secret digits which may be shared or observed.
Integrate a wide range of biometric solutions and technologies, customer applications and databases into a robust and scalable control solution for facility and network access
- Make it possible, automatically, to know WHO did WHAT, WHERE and WHEN!
1.6 ADVANTAGES AND LIMITATIONS
One advantage of finger-scan technology is accuracy. Identical matches are nearly impossible since fingerprints contain a large amount of information making it unlikely that two fingerprints would be identical. Fingerprint technology has another advantage offered by technology; the size of the memory required to store the biometric template is fairly small. There are some weaknesses to finger-scanning, most of which can be mitigated. There is a fraction of the population that is unable to be enrolled. There are certain ethnic groups that have lower quality fingerprints than the general populations. Testing has shown that elderly populations, manual laborers, and some Asian populations are more difficult to be enrolled in some finger-scanning systems [3].
Another problem is that over time, sometimes in as short a period as few months, the fingerprint characteristics of an individual can change, making identification and verification difficult. This problem is seen with manual
workers who work extensively with their hands. There are also privacy issues attached to finger-scanning technologies. Some fear that finger-scans may be used to track a person‟s activities. Others fear that data collected may be improperly used for forensic purposes. Paying with a government meal card at checkout instead of with cash would identify the student as a program recipient. The solution was for the school to provide students the option of using a finger-scan peripheral to purchase meals [3]. At the end of each month, a bill is sent to their parents for payment or to the free food program for reconciliation.
1.7 APPLICATIONS OF THE PROJECT
- Industrial application:“Fingerprint authentication system” project can be used by the employees, staff or workers in various industries like Automobile industries, manufacturing industries, Software development companies.
- Home or domestic application: This project can be used to automate the door locking process at our home, so the user need not to carry the door lock keys along with him, he can just use his/her finger to open the door.
- Bank Lockers or security safes: Many of the banks use key based or password based locks for their lockers or safes. We can implement Fingerprint based bank locker system using this project.
1.8 PROJECT WORK ORGANIZATION
The various stages involved in the development of this project have been properly put into five chapters to enhance comprehensive and concise reading. In this project thesis, the project is organized sequentially as follows:
Chapter one of this work is on the introduction to this study. In this chapter, the background, significance, scope, objective, limitation and problem, advantages of this work was discussed.
Chapter two is on literature review of the study. In this chapter, all the literature pertaining to this work was reviewed.
Chapter three is on design methodology. In this chapter all the method involved during the design and construction were discussed.
Chapter four is on testing analysis. All testing that result accurate functionality was analyzed.
Chapter five is on conclusion, recommendation and references.
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