Sithole Thesis - UNIVERSITY OF ZIMBABWE

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UNIVERSITY OF ZIMBABWE

DEPARTMENT OF COMPUTER SCIENCE

Integrated Improved Security System Techniques in Combating Crime

Using the Biometrics at the National Airport of Zimbabwe

GODFREY SITHOLE R9917454

Supervisors : Dr G. T. Hapanyengwi

Mr O. Kufandirimbwa

This dissertation is submitted in partial fulfillment of the requirements for

the degree of Masters of Computer Science in Computer Science

17 AUGUST 2010

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ACKNOWLEDGEMENTS

Firstly and foremost, I would like to thank my sweetheart Chiedza Sithole for her

patience and understanding during the many hours I disappear and become

antisocial. My heartfelt thanks also go to Dr G. T. Hapanyengwi and Mr O.

Kufandirimbwa my project supervisors, for their patience and guidance over the

course of the project.

I would also like to express my gratitude to Professor Mafongoya, Dr Mahamadi,

Dr Nyaruwata and Mr Rupere for their support to the completion of this project.

My gratitude also go to Mr B Nyambo the Chairperson of the University of

Zimbabwe Department of Computing Science for arranging project seminars for

us. I would like to thank Mr R. Sidimeli, Mr C. Mukwandara , Mr E. Sambana ,

Mrs G. Chirwa and Mrs P. Mushangwe of the same department for their

assistance with access to the department resources.

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DEDICATION

TO MY SON GODFREY FIDEL

WITH LOVE

TO MY MOTHER, MRS E. SITHOLE AND MY BELOVED FATHER, THE LATE

MR A. M. H. M. SITHOLE, I MISS YOU.

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TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION

1.1 Background Information and Problem definition 11.2 Aim and Objectives 71.3 Scope of the study 71.4 Research Problem 81.5 Justification of the study 81.6 Overview of the thesis 8

CHAPTER 2: LITERATURE REVIEW

2.1 Introduction to review on Biometrics 102.2 Advantages and Disadvantages of Biometrics 182.3 The Properties of Biometrics 202.4 Fingerprint Matching 212.5 Fingerprint Limitations 222.6 Fingerprint Matching techniques 24

CHAPTER 3: REVIEW AND ANALYSIS OF EXISTING ALGORITHMS

3.1 Minutia Matching 273.2 Existing Matching Algorithms 283.3 Pattern based (or image-based) Algorithms 293.4 Optical 293.5 Disadvantages 303.6 Ultrasonic 303.7 Capacitance 313.8 Passive Capacitance 323.9 Active Capacitance 323.10 Minutia Matching Algorithm 333.11 Process in existing matching algorithm 333.12 Disadvantages of the existing system 343.13 Architecture of the proposed algorithms 343.14 Operations of the proposed matching algorithms 353.15 Architecture of the proposed system 363.16 Requirements of the system 373.17 Outputs 373.18 Inputs 383.19 Processes 383.20 Performance /Complexity 393.21 Non- Functional Requirements of the system 393.22 Scalable 403.23 Conclusion 40

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CHAPTER 4 CONCEPTUAL DESIGN

4.1 Introduction 424.2 Current Operations 424.3 Architecture of Existing system 434.4 Proposed Integration improved minutia algorithm 44 4.5 Proposed Solution Architecture 454.6 Components of the architecture 454.7 The Algorithm 464.8 Alignment of point patterns 484.9 Align Point Matching 484.10 The Experimental results 484.11 The user Interface 50

Chapter 5 System Implementation

5.1 Introduction 525.2 Implementation and Programming Language used 525.3 Implementing Security 535.4 Maintaining Data Integrity 535.5 Referential Integrity 5.3

Chapter 6: Testing and evaluation of the Integrated Improved security system techniques in combating crime using the Biometrics.

6.1 Material View and Simulation 546.2 Black Box Testing 556.3 Integration testing 556.4 User Interface testing 556.5 Output testing 556.6 Walkthrough testing 56 6.7 Evaluation of the Integrated Improved security techniques 57

Chapter 7: Conclusion and Suggestions for future work

7.1 Introduction 587.2 Evaluation 587.3 Limitations 587.4 Suggestions for future work 597.5 Recommendations 60

Chapter 8: System Output(Simulation , Interface, Components)

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Figures:

Figure 1: Fingerprint patterns.Figure2: Architecture of the proposed system.Figure3: Architecture of the existing system.Figure4: Minutia Extraction.Figure5: User Interface.

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Tables.

Table 1: Advantages and Disadvantages of Biometrics.Table 2: Technology ,Advantages and Disadvantages.Table 3: Matching Results.

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Diagrams61-111

REFERENCE 112 -115

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ABSTRACT

Biometrics have become very popular as a tool in combating crime in the world.

This has also been necessitated by the September 11 2001 event. Despite all

the research that has been carried out the improvement of the algorithms still has

not been exhausted.

In the past research community has focused primarily on the password, and

national identity cards and biometrics with less effective algorithms. Certainly

there are scenarios that clearly favour one approach over the other. However it

is my belief that in any of the current and future complex crimes will require better

algorithms with improved time and space complexities.

Firstly the algorithm is subjected to the fingerprint authentication. The results are

recorded. Then the algorithm is improved and better results were achieved.

Surprisingly, extremely little research to date has considered continuous

systematic and logical improving the algorithms to achieve authenticated results.

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CHAPTER 1

INTRODUCTION

1.1 Background information and Problem definition

Providing security to any place is a major concern for an organization or

country. People had resorted to different methods of securing their property

by building durawalls, electric fences, burglar bars to mention a few. The

main idea behind is for the property not to be used without the consent of the

owner. Some scholars refer using somebody’s knowledge without his /her

consent as stealing. However security refers to different forms of safe

environment. According to Maslow Highrachy of needs also mentioned

security as a major concern.

There has been a surge of work in the area recently due to increased

demand from customers. There have been many world events that have

directed our attention towards safety and security. In particular the tragic

event of September 11 2001. This event had increased the attention to

security in airports as well the general environment. Most of the attention to

security has been obvious such as improved screening of peoples access to

particular places. Does visible security actually aid computer attackers or

terrorists who play close attention to the development of such security

techniques? Would we feel safer if security were transparent to us or would it

be an invasion of privacy?. Then what about combating crime using the non-

biometrics and biometric techniques.

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This study will look at integrated improved techniques to combat crime using

the biometrics. Now it is important to provide a few details about some

aspects of international crime in the world. The organized crime is together

with terrorism, a major threat to our society. In contrary to terrorism, criminal’s

have no interest in acting publicly. That makes it difficult to fight and prevent

crime.

There are a series of factors such as

The international dimension

The sophisticated and flexible group structures.

The use of legitimate business

The degree of specialization

The attempt to influence decision

Non- biometrics refers to the identification of as person using the passwords and

identity cards amongst others. Biometrics refers to the identification of a person

based on his or her physiological on behavioral characteristics. Today they are

many biometrics devices based on characteristics that are unique for everyone.

Some of these characteristics include, but not limited to fingerprints, hand

geometry and voice . These characteristics can be used to positively identify

someone. Many biometrics are based on the capture and matching of biometrics

characteristics in order to produce a positive identification. A good example is

that if that if we place a biometric device or systems of devices at the Harare

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International Airport will be able to detect who comes in or who goes out with

criminal offences.

With every system, there are vulnerabilities that someone, if given a chance will

take advantage of . Currently, Zimbabwe is using passwords and identity cards

as a form of identification. Now it is easy to talk about vulnerabilities and to take

advantage of those vulnerabilities, but if we are aware of them, we may be able

to improve the security system that mitigates such weaknesses.

The disadvantages of passwords and identity cards is that they can be used by

somebody if stolen without the owner’s consent. In general every biometric

device or system of devices includes the following three processes enrollment,

live presentation and matching. The time of enrollment is when the user

introduces his or her biometric information to the biometric device for the first

time. The enrollment data is processed to form the stored biometric template.

Later during the live presentation user’s biometric information is extracted by the

biometric device and processed to form the live biometric template. Lastly the

stored biometric template and the life biometric template are compared to each

other at the same time of matching to provide the biometrics score in results.

Each of these processes is discussed in detail including possible faults. In this

study we will concentrate on the matching process and to improve the algorithm.

This also applies that the matching can be done by a human being as in the

issue of identity cards.

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The use of violence and the counter measures applied by organized crime

groups. The above all indicate the strength of crime activities of well organized

criminal groups.

The crime areas that seem to have appealing are organized crime groups

across most African states with Zimbabwe included are

During trafficking especially, the production and trafficking of synthetic

drugs

The exploitation of human beings and illegal migration.

Fraud

United States of America dollar Counterfeiting

Commodity counterfeiting

money laundering

The scale and the typology of the crime phenomena vary within African

according to the country and the region. Therefore it is necessary to take into

account these variations at a regional and international level, when establishing

a coordinated response both for preventative and repressive actions.

People had resorted to the use passwords technology and global events has

significant impact on the world today. A more interactive and virtual society have

emerged through the use of the internet and as a result, has exposed

individuals and business to a host of security issues . Because of this securing

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and protecting valuable data and our identity have become areas of great

concern and cannot be ignored.

Clearly it has become critical in today’s environment to implement ways to

increase security levels. Maintaining and managing access while protecting both

the user’s identity and the computer’s data and systems have become

increasingly difficult .However no security is hundred percent efficient. But

nevertheless its my belief that integrated improved security system to compact

crime using biometrics will emerge as one of the most important aspects in

combating crime in today’s world.

Clearly it has become critical in today’s environment to implement ways to

increase security levels. Manufacturing and managing actors while protecting

both the user’s identity and the computer’s data and system has become

increasingly difficult.

However no security is hundred percent efficient. But nevertheless, its my belief

that improve security system to combat crime using biometrics is one of the

most important aspects in combating crime, in today’s world.

Surprisingly, extremely little research has been considered, the numerous

technical problems associated with the improved algorithms used in the matching

process either in non- biometric or in the biometrics.

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1.2 Aims and objectives

The aim of this research is to investigate the appropriateness of integrated

improved security system techniques in combating crime using the biometrics. It

is also the aim of this study to improve the algorithms used in the matching

process. To explore crime campaign awareness as other form of security

techniques. To evaluate the appropriatness and to test and analyze the

effectiveness of the integrated improved security system approach to combat

crime using the biometric.

1.3 Scope of the study

The importance of integrated improved security system techniques in combating

crime brought me to one of the aims of my study to improve the algorithm in the

matching process.

It is also in this research that the researcher will focus on other security system

techniques that need to be outlined in combating crime such as crime campaign

awareness. Since one of the requirements is to make people aware of the crimes

they commit on daily basis.

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1.4 Research Problem

To investigate the effect or applicability of the integrated improved security

system techniques used in combating crime in the matching process.

1.5 Justification of the study

The security system research community has focused primary on the use of

passwords and identity cards to combat crime separately. However it is my belief

that many of the complex, large scale crimes committed today may require the

integrated improved security system techniques approach. This ideal security

system techniques to handle such complex crimes will be one in which criminals

will find it difficult to get away with crime.

On the other hand, one of the requirements of the following security systems

technologies is to reduce crime and people are aware of it using the crime

campaigns awareness.

1.6 Overview of the Thesis

The structure of the rest of the report will be as follows: in chapter 2 we discuss

the major principles of the biometrics and the major research that has been

carried out in the area. In this chapter we look at the important terms used in

biometrics. In chapter 3 we discuss the review and analysis of the algorithm

used. Chapter 4 describes the conceptual assignment of the proposed algorithm

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for the fingerprint authentication. The data simulation is dealt with in chapter 5.

The testing and evaluation of the efficiency of the algorithm are dealt with in

chapter 6. Chapter 7, deals with the conclusion and evaluation of our findings

and the suggestions for future works found in the chapter.

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CHAPTER 2

LITERATURE REVIEW

2.1 Introduction to review on Biometrics.

The biggest challenges facing the Harare international Airport today is

confirming the true identity of a person. However there are several

identification verification schemes that exist today but the most accurate

identification schemes are in the area of Biometrics. The reason is that

physiological characteristics of a person cannot be used by another person.

It follows that the identity cards can be used by another person if lost or

stolen. Furthermore the matching process is made difficult if the person is aging.

Even if there is the recent and best algorithm it cannot detect the identity

of the person in the identity area. Though the identity cards can be changed

regularly but the problem is not solved.

Consider an example of an ATM card. The person wishes to use the ATM

card, is required to enter in a personal identification number (PIN) in order

to begin the transaction(s). The type of identification verification is given by

what the person has on the card. The fact is that the person knows the PIN.

But looking at the current situation there may be a potential problem to the

ATM scheme given above. There are various scenarios, the card could be

stolen. It is difficult for the thief to use the ATM card unless she / he knew

the PIN, But let us remember that the PIN is vulnerable to theft especially

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if someone is looking over the shoulder while entering the PIN number.

This example shows that crime is difficult to control. So using Biometrics such

as fingerprints alone it is difficult to eradicate crime. So this suggest the

importance of Biometrics should be used with another method to combat

crime. The appropriate technique is the crime campaign awareness. The

individual is made known to him/her before the commission of the crime.

Then those who did not understand the crime campaign awareness are

then detected by an improved algorithm in the matching process. So these

campaigns must be at different forums such as, the radio, the media, and

by the police officers at the National airport of Zimbabwe.

These different Biometrics characteristics are used for identification. The

domain include fingerprints, hand geometry, retina and iris patterns, facial

geometry, signatures and voice recognition. Now the current situation has

demonstrated that Biometrics are preferred over the traditional methods

such as the passwords and the identity cards. The main reason had been

mentioned earlier in their thesis. The interesting thing in dealing with

Biometrics identification is that, the individual to be identified is required to

physically be present at the point of identification and furthermore the

identification based on biometric techniques does not depend on the user to

remember a password or carry a token [1].

Two distinct function for biometric derive include that to prove you are who

you say you are and to prove you are not who you say you are not. The

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main purpose of the first function is to prevent the use of a single identity by

multiple people. It assist for a possible criminals to use the National Airport

to go to other countries for fear of arrest. Now it is important for the

biometric device be able to differentiate between a live biometric presented

to the scanner i.e. a real finger or a spoofed biometric trying to fool the

scanner.

This thesis will concentrate on improving the algorithm in the matching stage

.The other mentioned function is used to prevent the use of multiple identities by

a single person [1].Then must be ensured that the biometric system either

automatically cross checks the enrolled characteristics for duplicate and

utterance does not allow a person to register their biometrical i.e fingerprint under

two different names.[1]

Crime campaigns awareness must be used to sensitive individuals on the crime.

Now to provide improved security biometrics could be used in addition. This

helps reduce the number of people committing crime. The Biometrics has been

around for many years. The French anthropologist Alphnse Bertillon devised the

first widely accepted scientific method of Biometric identification in 1870 in

fingerprint aunthentication. . The Bertillon system Bertillonage or anthropometry

was not based on fingerprinting but rather relied on a systematic combination of

physical measurement .The measurements included measurements of the skull

width foot length and the length of the left middle finger combined within hair

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colour, eye colour as well as face and profile pictures. The next thirty years

Bertillonage was the primary method of biometric identification [2] The other

example of biometric in practice was a form of fingerprinting being used in China

in the 14th century as reported by Joao de Barros , he wrote that the Chinese

merchants were stamping children’s palm prints and footprints on paper with ink

to distinguish the young children from one another [3] Now the problem of these

identification is the matching process You find that after a certain period the child

in old cannot match the previous foot. This is the reason why improving the

material is of special importance.

The fingerprints are unique to each individual and each individual. Has his / her

pattern in the fingerprints. The police in the developed countries have

successfully used Biometrics to capture criminals and also finding missing

children. The fingerprint records the patterns found on a fingerprint. The

pattern matching is the one I feel need to be improved [4].

The fingerprint serve to reveal an individual’s true identity. This methods as

means of identification has been helpful. The idea is that fingerprints are

unique and has not been any type of pattern duplication by two different

people. The other point is that each individual has always his/her

fingerprints. The problem of stolen and cost in covered. The uniqueness

applies to the identical twins, triplets, quadruplets and the quintuplets

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furthermore any type of burn (superficial), abrasions, or cuts do not affect

the ridge structure, and hence the fingerprint pattern is unaffected. [5]

The hand geometry his/her analysing and measuring the shape of the

hand. The good thing is that it is relating easy to use. Since it is easy in

integration into other systems and process coupled with easy of use, then

makes it the fundamental step for many biometric projects. The problem is

that the hand geometry could be changed by smashing it with a hammer.

[3]

There have been six different hand- scanning products developed over this

span, including some of the most commercially successfully biometrics to

date [6]. The hand geometry biometric is by far less accurate than other

biometric methods. San Francisco International Airport, the USA’s fifth largest

airport has been using the hand geometry based systems to authenticate

the employees for almost 10 years [6].

The U.S federal Bureau of Prisons uses the hand geometry to identify

convents of its prisoners, staff and visitors [6]. Once the individual enters the

system the hand must be scanned [2]. The information is entered into a

database and the individual is issued a magnetic swipe card he/she carries

all the time [4].

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The retina-based Biometrics includes analyzing the layers of blood vessels

situated at the back of the eye. It uses the low intensity light source through an

optical computer to scan the unique patterns of the retina[7].

The method has limitations if the individual wears glasses. The other

problem is if the individual in having a close contact with retinal reading

device. The other problem is that if the individual has an eye disease such as

cataracts. Unfortunately this type of biometric is not accepted by many

users[3].

The retina scan becomes one of the oldest biometrics as 1930’s research

suggested that the patterns of board vessels on the bank of the human

eye were unique to each individual. The First retina scan device made for

commercial use was in 1984 [8].

The Iris based biometric includes analysing features found in the coloured

ring of tissue that surrounds the pupil [7] . The biometric has the potential

for higher than average template matching performance [7]. The idea of

using iris patterns for personal identification was originally proposed in

1936 by ophthamologist Frank Burch. In 1980 the idea had already

appeared in James Bond films. This demonstrates that it remained

schemes function and conjectures. By 1987 two other opthalmogists Aran

Jafis and Leonard Flom, patented the idea. In 1989 John Daugman was

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asked to create algorithms for the iris recognition [7]. The algorithms which

were patented in 1994 and are owned by Iridian technologies [7]. So the

issue of algorithm in the biometrics is of great significance.

In 1999, EyeTicket Corporation introduced Jetstream for passenger

processing including the airline. The method was used at the check in and

boarding , passport and visa control. The EyeTicket’s Jetstream and

EyePass programs operating at Charlotte Douglas International airport,

USA, at Heathrow airport, UK and elsewhere have accumulated in excess

of 400 000 transactions with 100% accuracy, no false identification , and no

security breaches [7]. The facial recognitions considers analysing the facial

characteristics as the case in the overall facial structure which includes the

distance between the eye, nose, mouth and jaw edges. The methods

worked together with digital video camera that captures the images of the

face . The methods had been widely used. The technique recorded

potential threats and so far has been improved in high-level usage. The

method of facial recognition started late 1980. The method was commercially

available systems were made in the 1990s [9].

However many peoples first heard about the facial recognition after

September 11th 2001. The football fans were introduced to it at the super

Bowl several years before the September 11th 2001.[10].

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The biometric signature verification is beyond the visual signature

comparison in its analysis of the way a user signs his/her home.[11].

However there are signing feature such as speed, velocity and pressure are

important as the finished signature verification devices are reasonably

accurate in operation. Though every person has a unique signature but that

signature is still vulnerable to duplication by thieves. The common

phenomenon is that if, one person tries to “forge” a signature he/she will

study the victim’s signature and practice that style of writing. Remember that

the attacker needs to know the variables such as speed, velocity and

pressure prior to attempting to forge a biometric signature [12]. The method

used to was simply working at two or more samples of a person’s

signature to see if they matched . This was called signature verification.

The method is widely used in Zimbabwe in the banks. Now the use of

digital signature verification is done by comparing the movement of how

one signs his/ her name.

The voice authentication considers allowing the user to use his/her voice

as an input device to the system. The voice commands the computers

began with application that were trained by the user to recognise certain

words that were spoken that the user can speak to a word processor

instead of actually typing the words out [13]. The problem with this

method is that poor quality and ambient noise can affect verification .

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However certain voice-scan technologies are resistant to imposter attacks

to a lesser degree than finger scan systems [14].

Biometrics has long been used in the identification beginning with the early use

of finger prints with the new technology will then be able to use devices that use

curve accurate in the biometrics [3]

2.2 Advantages and disadvantages of Biometrics

Currently biometrics offer much security but as compared to a Pin or a password

.The biometrics holds a set of advantages and disadvantages in general. The

table below indicates the properties [15]

Table 1.

Advantages Disadvantages

Positive Identification Public acceptance

You can’t lose, forget or share your

biometrics information.

Legal issues

A biometrics template is unique to

the individual for whom it is created.

Possible increase in hardware cost to

current systems

Rapid identifications/authentication May require large amounts of storage.

Costs in general are decreasing Privacy concerns

It is clear that the advantages outweigh the disadvantages. The reason is that

the main aim is to obtain positive identification [7], it is difficulty to falsify a

biometric trail of an authorized user, biometric (e.g. face or finger print). A good

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example is that finger prints are left in a wide variety of places in a given day

such as at homes and offices.

Individual has his/her biometric traits put into a template for later identification/

verification it becomes a unique template. The major problem is public

acceptance when implementing a new system or methods by which one abides

[16] The issue is that the public does not accept it then the fingerprint would be

difficult to implement successfully because it would not be used. Currently there

is a long list of legal resources that fingerprints imposes. The issues is that legal

issue are also taken into consideration in this study [17]

The hardware costs definitely increases and that becomes a constraint for any

agency or enterprise for to use fingerprint as a means for identification/

authentication. So the cost of the dynamic technology always become an issue.

The other thing is the storage allocation of biometrics templates also increase.

The table below indicate the fingerprint with the technology [18].

Table 2.

Technology Advantage Disadvantage

Fingerprint scanning/

matching

- Inexpensive

- Very secure

- physical contact to a

general scanning device

may spread germs

The fingerprint watching offers a very secure means of identification in an

inexpensive way [19] The draw back in that there is contact with general a

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scanning device that may propagate germs. So these is cost a in offering

antibacterial cleansing solution before and after each individual means his/her

fingerprint may reduce the problem [20]

2.3 The properties of biometrics

The automatic capturing (ie enrollment or authentication) of biometrics sample

data and comparison (ie matching with previously stored characteristics or

normative data requires the following properties of biometrics characteristics.

Invariance: Biometric properties should be constant over a long period of

time ie fingerprints taken during the issuing of national identify cards. Once

this is done it eliminate the need for constant updating of the template that are

stored in the system. The finger print is constant throughout an individual’s life

time as compared to facial characteristics which may change normal due to

aging .

Measurability and Timeliness: The individual properties must be able to be

automatically matched to an expected norm. The fingerprint sample should be

suitable for captured without wasting time which is important, for continuous

authentication and other complications because of the use of a technique

which will provide near real –time verification. The airport fingerprint

verification system needs to be able to capture fleeing criminals from or to

Zimbabwe.

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Singularity: The fingerprint characteristics should have sufficient unique

properties in order to differentiate one individual from another . The case is

true for fingerprints.

Reducibility: The stored data should be able to being reduced to a size that

is easy to handle but impossible to duplicate. The characteristic is important

especially when dealing with communicating the finger print data across

secure chancels (ie from verification device to the controller of the results

which may be in a remote area.)

Reliability. The fingerprint matching technique should ensure high reliability

and integrity. The airport matching system need to be reliable since, it would

be costly to have a system that does not provide consistent result.

Privacy : The fingerprint technique should ensure the privacy of the person

using the system so that their privacy is not being violated in any way [21]

2.4 Fingerprint Matching

Every individual posses a unique fingerprint from any other person. So the

fingerprint verification are based on two basic properties, the invariant and

singularity. The fingerprint verification has been used for a long time and

routinely used in forensic laboratories and identification units all around the

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worlds. The fingerprint evidence has also been accepted in courts of law for

nearly a century [7]

The whole world is familiar with fingerprint verification methods. The universality

makes this tactic have a high user acceptance rate. My experience was to use a

fingerprint scanner while applying for the new National identity card at Market

Square in Harare. The device was easy to use and the identity card was issued

to me without delay.

The step that followed was enrolling into the system, but then avoided the

matching process since I am not a criminal. I used, an optical scanner to get the

identify card. Also checked the monitors to free the resulting template.

Finger patterns can be represented by a large number of features [31]. The

common pattern including the overall ridge flow pattern, frequency, location and

position of singular points.

2.5 Fingerprint Limitations

The fingerprint matching method contains influences that may affect the outcome

of the verification process some of the constraints are [13]

Fingernail growth may have an effect on how firmly the user is able to

place his/her finger on the matching device. It may result in inaccurate

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results from the device as the user may be rejected by the system. This

covers the use of artificial nails that the user may apply to real fingernail.

Fingerprint fitness also have an effect on how the devices is able to pick

up details of the fingerprint. On this it depends on how well the depth and

the spacing of ridges are on the users finger. The constraint is controlled

by the user so proper enrollment from the beginning needs to be done.

Then also a proper placement of the finger on the matching device at the

time of verification, most common is that there is a fingerprint- matching

device that alleviate the problem by offering a sensitive “’touching area” for

the users.

The condition of the fingerprint also have an effect on the outcome of the

matching device because the user may have dry cracked, or damp

fingers. The issue is that suppose user has dry, cracked, or dump fingers

at the time of enrollment at the time of verification the matching algorithm

may not be sensitive to compensate for the differences . The other

obstacle is the scars and/ or scratches on the fingertips of the user. The

scars and scratches depending on the location obstruct some important

properties of the fingerprint that the matching device is seeking for to

extract. Some cases the matching device may be able to use to scar on

the fingertip as part of the properties to be extracted .

Temperature of the user’s finger or hand. It has been noted that the

temperature cause inaccurate results from the matching device. Personal

in June 2010 the matching device continuously reject me in the morning

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because they fingertips are cold. The matching device does liveness tests

based on temperature of the finger rather than on a pulse on the

fingertips.

2.6 Fingerprint matching techniques

The techniques/methods applied to gather fingerprint information has changed

greatly over the years. Sophisticated fingerprint matching methods have

emerged since the beginning of this techniques of verification. Some

complicated techniques available are [22]

Optical sensors with CCD or cmos camera. The fingerprint is placed or

pushed on a plate and is eliminated by a LED light source. Then through a

prism and a system of lenses, the image in projected on a camera. The

frame grabber technique are used and the image in stored and ready for

analysis

Ultrasonic sensors: Using ultrasonic sensor, a scan of the fingerprint with a

resolution of about 500 dots per inch in possible.

The technique in able to offer templates which are full of useful detail of finger

print information.

Electronic field sensor: The method creates an electric field with which an

array of pixels can measure variations in the election field that are caused by

the ridges and valleys in the fingerprint

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Capacitive sensors: The method is similar to electronic field sensor except

that when the finger in placed on the sensor an array pixels measures the

variations in capacity between the valleys and the ridges of the fingerprint

Temperature Sensors: The method makes distinction between the

temperature of the ridges and the temperature on the valley on the fingerprint.

A temperature match can be taken by simply swiping the finger over the

sensor.

The methods seem very advanced and accurate. Now it is still possible that a

desperate attacker may attempt to spoof a legitimate user by creating fake

fingers. The fake fingers can be made both by the cooperative of the legitimate

user (ie for testing methods) or without the cooperation of the legitimate use by

lifting a fingerprint off a keyboard or coffee mug. The traces of fingerprint are

known as latent fingerprints. Tsutomu Matsumoto a Japanese cryptographer has

discovered a means to fool many of the commercial fingerprint matchers

available using common ingredients [23].

One of Matshumoto’s more interesting experiments involves latent fingerprint.

He takes a fingerprint left on a piece of glass enhances it with a cyanoacrylate

adhesive and photographs it with a digital camera . Then using photoshop he

improves the contrast and print the fingerprint onto a transparency sheet. Then

he takes a photo sensitive printed circuit board (PCB) and uses the finger print

transparency to etch the finger print into the copper, making it three dimensional.

34

Finally he makes a gelatin finger using the print on the (PCB) This fools

fingerprint detectors about 80% of the time [17]

35

CHAPTER 3

REVIEW AND ANALYSIS OF EXISTING ALGORITHM

3.1 Minutia Matching

Given a diverse set of fingerprints of criminals in the criminal investigations

Department at the National Airport of Zimbabwe it is difficult to make the correct

match. The sound decision making will to an increasing extend rely on the

matching algorithm [27]

Matching algorithms systems does not only rely on the patterns of the finger

print such as the arch pattern, the loop patterns and the whorl pattern [28] The

figure below show the three patterns.

The arch Pattern The loop pattern The whorl Pattern

Figure 1

Even though some algorithms had looked to the major minutia features of finger

print ridges are: ridge ending , bifurcation and short ridge (or dot). The ridge

ending is the point at which a ridge terminates. Bifurcations are points at which

36

a single ridge splits into two ridges. Short ridges (or dots) are ridges which are

significantly shorter than the average ridge length on the fingerprint. According

to the previous algorithms these are characteristics which were well considered

[28]

Therefore we aim at exploiting matching algorithm which integrate the minutiae

and the patterns for the authentication of the finger print. The reason is no two

fingers have been shown to be identical [30]

Our research effort in the matching algorithm focuses on ensuring that all the

seven characteristics of the fingerprint are incorporated in the matching

algorithm. Our research should result in applications that will make it easy for

users unfamiliar with matching algorithm system to detect more criminals.

This chapter sees to give details on the matching algorithm of the finger prints.

Now to understand better the matching algorithm it is imperative to look at other

applied matching algorithms. Attention will be made to the existing matching

algorithms.

3.2 Existing Matching algorithms.

The following are some of the various matching algorithms that exist.The

following list is just a few of the existing matching algorithms which make use of

the minutae matching.

37

3.3 Patterns based (or image- based) algorithms.

The pattern based algorithms compared the basic fingerprint patterns (arch,

whorl and loop) between previously stored template and a candidate fingerprint.

This requires that the images be aligned in the same orientation. The algorithm

finds a central point in the central fingerprint image and centers on that. The

candidate fingerprint image is graphically compared with the template that

determines the degree to which they match [31].

The above method uses the furthering fingerprint sensors. A finger sensor in an

electronic devise used to capture a digital image of the fingerprint pattern. The

captured image in called a live scan. The live scan is digitally processed to

create a template. A biometric template (collection of extracted features) which is

stored and used for matching for authentication purposes [31]

3.4 Optical

Optical fingerprint imaging involves capturing a digital image of the print using

visible light. The type of sensor is in essence a specialized digital camera. The

top layers of the sensor where the finger is placed is known as the touch surface.

Beneath this a layer is a light emitting phosphor layers which illuminates the

surface of the finger. The light reflected from the fingers passes through the

phosphor layer to an array of solid state pixels (a change - coupled device )

which captures a visual image of the fingerprint. The scratched or dirty touch

surface can cause a bad image of the finger print.[31]

38

3.5 Disadvantage

The disadvantage of this type of senor is fact that the imaging capabilities are

affected by the quality of skin of the finger, The case is that a dirty or marked

finger is difficult to image properly . Then it is possible for an individual to erode

the outer layers of skin on the fingerprints to the point where the fingerprint in no

longer visible. This can be easily fooled by an image of a finger print if not

coupled with a live finger’ detectors. However, unlike capacitive sensors, this

sensors technology is not susceptible to electrostatic discharge damage [31]

3.6 Ultrasonic

Ultrasonic sensor makes use of the principles of medical ultrasonograph in order

to create usual images of the fingerprint. Unlike optima imaging , ultrasonic

sensor use very high frequenting sound waves to penetrate the epidermal layer

of skin. The sound waves are generated using piezoelectronic transducers and

reflected energy is also measured using piezoelectric materials. Then since the

dermal skin layer exhibits the same characteristics pattern of the fingerprint the

replaced waves measurements can be used to form an image of the finger print.

It eliminates the need for clean undamaged epidermal skin and a clean sensing

surface.

39

3.7 Capacitance

Capacitance sensors utilize the principle associated with capacitance in order to

further fingerprint images. The two equation used in this type of imagining are:-

C = Q/V

C = ξ0 ξr A/d

Where

C is the capacitance in farad

Q is the charge in coulombs

V is the potential in volts

ξ0 Is permittivity of free space, measured in farad per metre.

ξr is the dielectric constant of the insulates used.

A is the area of each plane electrode measured in square metres.

d is the separation between the electrodes measured in metres.

The method of imaging the sensor array pixels each act as the plate of a parallel-

plate capacitors, the dermal layer (which is electrically conductive) acts as the

other plate, and the non-conductive epidermal layer acts as a dielectric.

40

3.8 Passive Capacitance

The passive capacitance sensor uses the principle image of the fingerprint on

the dermal layer of skin . Each sensor pixel is used to measure the capacitance

at that point of the way . The capacitance varies between the valleys of the finger

print due to the fact that the volume between the dermal layer and the sensing

element in valleys contains an air gap. The dielectric of the epidermis and the

area of the sensing elements are known valid the measurements of capacitance

values. Then they are used to distinguish between finger print ridges and valleys.

[31]

3.9 Active Capacitance

The active capacitance sensor uses a changing cycle to apply a voltage to the

skin before measurement takes place. The application of voltage charges the

effective capacitor. The electric field between the finger and sensor follows the

pattern of the ridges in the dermal skin layer. On the discharge cycle the voltage

across the dermal layer and the sensing element is compared against a

reference voltage in order to calculate the capacitance. The distance values are

then calculated mathematically using the above equations and used to form an

image of the fingerprint. The active capacitance sensors measure the ridge

patterns of the dermal layers like the ultrasonic method. It also eliminates the

need for clean undamaged epidermal skin and a clean sensing surface.

41

3.10 Minutia Matching Algorithm

This method uses for each detected minutia uses for each detected minutia ,

then realizes the following parameters.

1. x and y coordinates of the fingerprint point.

2. The orientation which is defined as the local ridge orientation of the

associated ridge.

3. The type of the fingerprint point that is whether the minutia is ridge ending

or ridge bifurcation.

4. The associated ridge is represented by points sampled at the average

inter- ridge distance along the ridge linked with the corresponding

fingerprint point [32]

3.11 Processes in existing matching algorithm

The existing algorithm is based on the following 3 steps.

1. There is live presentation of the finger print to the scanning machine

2. The template is formed.

3. The matching process is done.

We refer to the matching as the pattern based algorithm. The reason in that the

matching algorithm is biased toward the three patterns (i) arch (ii) loop and whorl

with little consideration on the minutia of the fingerprint. The matching algorithm

continuously does the matching in this category.

42

3.12 Disadvantages of the existing system.

1. The matching algorithm did not realize all the principle of minutiae such

as

- ridge ending

- bifurcation

- Lake of enclosure

- Short ridge

- Dot

- Spur

- Crossover or bridge

The matching algorithm used the Cartesian Coordinates.

3.13 Architecture of the proposed algorithms.

Now looking at the nature and the operations of the existing system, the users of

the previous algorithms are one who need the most recent matching algorithm.

At this point depending on the nature or the classes of the users the proposed

matching algorithm has to provide a complete service to the decision makers

(Users).

43

3.14 Operations of the proposed matching algorithm

The proposed solution will be to create the matching algorithm that uses the

polar coordinates and uses and the minutiae of the fingerprint. The matching

algorithms requires, fingerprint scanner, minutiae extraction database (template)

Minutiae matching and the final the results.

44

Server

3.15 ARCHITECTURE OF THE PROPOSED SYSTEM

template

Client

Figure 2.

Finger print scanner

Minutia extraction

Data Base

Finger Print

Template

File List

Secure Files

Decrypt and verify user

Extract secure file

Provide Finger Print

Image

Calculate and encrypt fingerprint features

Access Derived.

Access granted let of secure files

Secure file Displaced

Finger print scanner

Minutia extraction

Minutia extraction

45

3.16 Requirements of the System.

System requirement is a characteristic or feature that must be included in a

matching algorithm systems so that the matching process takes place. The

matching algorithm must be accepted to the users. Matching algorithm

requirement therefore serve as benchmarks to match the overall acceptability of

the authentication results. The system requirements fall into five general

categories; outputs, inputs, processes, performance and control.

3.17 Outputs

The system must give the matching score

The system must give a report of the matching force and the member of

template in the database

The system must give the narration number

The system must list the results on the Microsoft Excel interface.

The system must give the minutia input.

The system must give the minutia output

The system must draw the results on the Microsoft excel.

The system must match the input template with the template in the

database.

The system must be match to determine the relationship between the

number of templates in the database and the incoming template.

The system must be able to give the result as correct or incorrect

according to the matching algorithm.

46

3.18 Inputs

The system must allow the user to enter the scanned fingerprints by

opening the file.

The system must allow the user to select the fingerprint he/she wants to

verify or authenticate.

The system must allow the user whether to print or view, or choose on the

screen the report selected.

The system must allow the user to select the fingerprint to be

authenticated.

3.19 Processes

The system must follow the matching algorithm in order to authenticate

The system must allow the printing of all the required reports if requested

to print.

3.20 Performance/Complexity

The system must be of better complexity (O (nlogn)) than the previous n2.

The system must be able to use the following characteristics of the

fingerprint for matching: ridge ending, bifurcation, lake or enclosure, short

ridge, dot, spur and the crossover or the bridge.

The system must be able to realize the relationship between the Cartesian

and polar coordinates such as the following:

x = r cos θ, y = r sin φ

47

y

r

r sin φ

θ x

r cos θ

r = √y2 + x2

0, if x = 0 and y = 0

θ = arc sin (y/r), if x > 0

-arc sin (y/r) + π if x < 0

The system must allow user to add or remove the fingerprint in the

database.

The system create the error 0 if the fingerprint has been entered more

than once.

3.21 Non-functional Requirements of the System

Non functional requirements as the name suggest are those requirements which

are not directly concerned with the specific functions delivered by the system.

These may relate to emergent system properties such as reliability, and

scalability.

48

3.22 Scalable

The system must be able to be adjusted, the matching rate to meet the

organizational change, requirements in the future. The system if resources were

available to be implemented was suppose to operate for the next five years

without authentication problems.

3.23 Conclusion

The minutia matching algorithm are a specific class of algorithms used to support

organizational decision making activities. A well integrated and improved

algorithm helps decision makers on what they need to combat crime at the

National Airport of Zimbabwe. The typical matching algorithm that decisions

makers may need for their decision making are as follows:

Authentication of all the criminals on the wanted lists.

Verifying all people leaving or coming into the country.

Projected report on which type of crime is most prevalent.

Revenue on the Police clearance certificates by people willing to leave

the country.

To efficiently improve the matching algorithm from the existing pattern matching

algorithms leads to the approach in this thesis. My approach is to check the

weaknesses of the pattern matching algorithm and then come out with an

integrated improved minutia algorithm to combat crime using the biometrics.

49

In the next chapter, I give the conceptual design of the whole system making use

of the matching algorithms.

50

CHAPTER 4

CONCEPTUAL DESIGN

4.1 Introduction

The design methodology makes consideration for the system design: the process

of improving the integrated improved algorithm system will start with the context

diagram which shows the relationship between the system and its external

environment. In this chapter I will present the data flow diagram of the system,

the user interface and the entity – attribute relationships.

4.2 Current operations

The International Airport of Zimbabwe is one of the places that control the

movement of people from and to Zimbabwe. It also detects criminals who will be

leaving or coming to Zimbabwe. The people who are involved in this class travel

by air. At the moment the country uses the following air ports: National Airport of

Zimbabwe, Bulawayo and the Victoria Falls. The busiest airport is Harare

International Airport. This is where the central decision making process is carried

by respective decision makers. Each mentioned airport has its own method of

fingerprint authentication or verification. The authentication has been working

since the inception. The fingerprint authentication/verification, decision makers

used to produce statistics of criminals arrested by pattern matching algorithms.

The Police at the National Airport gets the fingerprints of the suspects from

Criminal Investigation Department (CID) at Corner Josiah Chinamano and 7th

51

Street. The CID gets the names of the suspects from the police stations in the

country. Then the pattern matching algorithm takes some time to do the

fingerprint authentication since the fingerprint(s) has several minutiae patterns.

The top management work under a lot of pressure when it comes to the end of

quarter or end of year.

Due to the fact that the authentication of fingerprints is slow lead to low detection

of the criminals. The other problem of the pattern matching algorithm is that it

uses Cartesian coordinates.

4.3 Architecture Of Existing System

Image

Fingerprint image image liveCapture processing template

Fingerprint imageCapture processing

Figure 3.

52

The existing pattern matching algorithm is based roughly on the following steps:

The authorized user introduces his/her fingerprint information to the

template.

The fingerprint is captured as the live template.

The image of the fingerprint information characteristics are extracted

which is represented in Cartesian coordinates.

The fingerprint then moves through processing using the pattern matching

algorithm tailored to match the fingerprint with that in the database.

The matching is done and the result displayed.

When the reports of the authentication are needed then, they are printed. The

above process is called the pattern matching algorithm since the authentication is

done using some of the characteristics of the fingerprints. The system does the

authentication from the sources each time. When the authentication is posed

this will result in inefficiency and delay in the verification especially when the

fingerprints are almost identical.

4.4 Proposed integration improved minutia algorithm

After making some considerations of a minutia authentication algorithm the

author found out that the following can be one of the most appropriate system

alternative to combat crime at the National Airport. The minutia algorithm will

help in the strategy for the decision makers for the National Airport.

53

4.5 Proposed Solution Architecture

The solution is to create an algorithm with a better time and space complexity.

Also the algorithm uses the polar coordinates. Then if the user invokes the

system to authenticate the algorithm does that using all the fingerprint features.

The solution has vast advantages since all the minutiae of the fingerprint are

considered. There is also the advantage of rotation alignment stage and the

matching stage.

The only major disadvantage is that the spoofed fingerprint made from

cyanoacrylate is not detected.

MinutiaExtraction database

Fingerprint fingerprint Scanner image Template

matching result

Fingerprint minutia minutia Scanner extraction matching

Figure 4.

4.6 Components of the Architecture

The ANSI/NIST – CSL 1 – 1993 and ANSI/NIST ITL 1a – 1997 process

the fingerprint image data.

54

The ANSI/NIST ITL 1a – 1997 specifies common format to exchange the

image data information between dissimilar assisted system or systems

made by different manufacturers.

ANSI/NIST ITL 1-200 Consolidation of ANSI/NIST-CSL 1-1993 and

ANSI/NIST – ITL 1a-1197.

ANS X9 84-2001 manages and securing biometric information for use in

the fingerprint capturing.

X9 84: specifies cryptographic massage formats and key management

techniques that is used for the fingerprint authentication, data integrity and

privacy for biometric matching.

The X9 84 standard: defines a set mandatory fingerprints characteristics

requirements to manage biometric information securely.

API – application programming interface in the Bio API specification

version 1.1 2001.

This is for the fingerprint input and output to the Biometric Service

Provider.

The wave/scalar quantization (WSQ 93) algorithm I is the FBI standard for

digital fingerprint compression.

CJIS – RS – 0010 FBI: is the fingerprint transmission.

55

4.7 The Algorithm

1. Match the ridge associated with each input fingerprint characteristic

against the ridge associated with each template characteristic and then

align the patterns according to the stages.

2. Change the specification of the template and input characteristics into the

polar coordinate system from the Cartesian coordinate system in respect

of the fingerprint characteristics. After this the alignment is done and the

two diagrams of strings are forward by concatenating each characteristic

in an increasing order of radial angles. The following inputs are

considered:

Pp = ((r1p, e1

p, θ1p)T … (rm

p, emp, θm

p))T

Qp = ((r1Q, e1

Q, θ1Q)T … (rN, eN

Q, θNQ))T

r: radius

e: radial angle

θ: the normalized fingerprint orientation

3. Match the resulting strings Pp and Qp with a modified dynamic –

programming described below to find the edit distance between Pp and

Qp.

4. Compute the matching score of the template and input fingerprint

characteristics as the minimum edit distance.

56

Mpq = 100 pair

Max {M, N}

N pair is the number of fingerprint pairs which fall within a given boundary. M is

the minimum edit distance.

57

4.8 Alignment of point patterns

All the fingerprint characteristics is associated with a ridge. The alignment is

then achieved by matching and aligning the corresponding fingerprint features:

then matching the corresponding normalized ridges, the relative pose

transformation between the input characteristics and the template can be

estimated. The estimated pose transformation, the input minutia can be then

translated and rotated to align the template minutiae.

4.9 Align Point Pattern Matching

When two identical point patterns are exactly aligned, each pair of corresponding

points are completely overlapping. The situation a point pattern matching can be

simply made by counting the numbers of overlapping pairs.

4.10 The Experimental Results

The system was tested on a number of fingerprints. The set of fingerprints were

downloaded from the internet. The fingerprints were stored in the folder. The

spoofed fingerprints were also downloaded. As already mentioned that the

weakness of the system was that did not identify the spoofed fingerprint. The

other problem was that when the results were posted to an excel document.

The set contains at least 10 images (380 x 380) per fingerprint from the internet.

In the actual context the scanner was supposed to be used and the manufacturer

identified.

58

The downloaded fingerprint varied in quality. Approximately 80% were of good

and satisfactory quality. The remaining 20% was of poor quality including the

spoofed fingerprint.

Nearly all the fingerprint in the test set was matched with other fingerprint in the

set. The matching was labeled correct when the matched fingerprint was among

the 80% correct and the option incorrect if they were from the 20%.

The observation was that the incorrect matching occur mainly to the fact that the

fingerprint images was of poor quality or spoofed.

Table 4.

Database Correct Incorrect Matching score

1 1048 N/A 91.349

2 161 N/A 85.506

3 166 N/A 83.506

4 N/A 184 47.875

The above diagram is an example of how results are shown during the matching

process. How ever the real diagrammes will be shown in the system out put

section.

4.11 The User Interface

The proposed system makes use of the graphical user interface which is user

friendly. The users with little or no computing experience can learn to use the

59

interface after a short period of training. The screen that appear when the

system is executed is where the user can select the fingerprint to authenticate.

Then add as many as the user wants using the option open in the same data

base. Then add one or more fingerprints to the database. There is also an

option of removing if the user had made a mistake. The other option is

authenticate to match the fingerprint in the database with the input. There is also

a review option where the results are posted to an excel sheet. On this sheet a

lot of function can be done with the results including drawing different graphs.

The user interface was designed taking into consideration the concept of human

computer interaction and user centered design. The system is developed for

users who are not computer experts and those who have little knowledge of

computers; the designed user interface is the most convenient for the given

proposed solution. This will make decision makers feel the benefits of using

computers as a tool for combating crime. The users do not face hassles in

operating the system.

On the system the important thing is to know how to load the visual studio 2005,

in case the computer does not have. The system does not require the use of

passwords. Below is an illustration of the user interface . The real user interface

will be displayed in the system out put section.

60

Polar Coordinates (Pp)

Polar Coordinates (Qq)

Template Minutiae

Input minutiae

Fingerprint Reader

Figure 5

The visual studio 2005 code will also be shown in the out put system section

Data Base

Scanner

Add

Remove

Matching

Computer

Finger Print Authenticate View Report

Exit

Normalized matching scoreDate Base

Incorrect Correct

61

CHAPTER 5:

SYSTEM IMPLEMENTATION

5.1 INTRODUCTION

In this chapter we discuss the implementation of the integrated improved security

system techniques in combating crime using the biometrics. At this stage of the

project, we give a detailed explanation of the system. The main limitation was of

the purchase of the hardware, software and the application systems.

Nevertheless the logical and systematic implementation steps in implementation

of the integrated improved system to combat crime using biometrics are the

following.

5.2 Implementation and Programming Language Used

The Integrated Improved System works perfectly with a user friendly interface to

the environment. The requirement of the system is that they are accessible to

users who have a limited knowledge of computer systems. It is imperative that

graphical, self-explaining tools that give easy access to the data, with little or no

training, be available to the users when the system is deployed. Then taking all

this into consideration we found that visual studio 2005 is one of the

programming environments that can provide such facilities. The visual studio

2005 allow coding of the integrated system application easier because of it’s

easiness to be used in programming. It therefore helps very much in coding

62

source codes that would help to manage and maintain the integrity of the pattern

matching algorithm.

5.3 Implementing Security

Database security involves restricting access to data. Unauthorized users should

not have access to any data while other users should not have full access to

certain data in the integrated improved system. This assist that the fingerprints

added into the database for use in the authentication process are not altered.

5.4 Maintaining Data Integrity

Protecting data integrity involves making sure that authorized users don’t add,

change or delete data that could make parts of the database invalid or

inaccurate.

5.5 Referential Integrity

Referential integrity was implemented in the system. Even if the user can add

the same fingerprint it will be recorded with 0 in the database and the minutiae

does not change. When authentication is done then only one of the fingerprints

is used to represent the duplicated fingerprints. The results are send to the excel

as only one fingerprint from the group.

63

CHAPTER 6:

TESTING AND EVALUATION OF THE INTEGRATED IMPROVED SECURITY

SYSTEM TECHNIQUES IN COMBATING CRIME USING THE BIOMETRICS

In this section of the project we cover the simulation aspects of the integrated

improved security system techniques. The aim is to simulate the functionality of

the integrated improved security system techniques if it meets the requirement

specified in chapter 3 of the assignment. The simulation also demonstrated

areas where the developed source code does not conform to the anticipated

system functionality.

The system was simulated using visual studio 2005 programming language.

This programming language is also a powerful as visual basic when designing

user interfaces.

6.1Materialized View and Simulation

The materialized views and the system were simulated with the aim of finding out

if it had correctly been simulated according to the requirements of the chapter 3.

The materialized views are also simulated for consistency and integrity. The

simulation was done as the system was being presented.

64

6.2 Black Box Testing

Functional or black box testing is an approach to testing where the tests are

derived from the program or components specification. Another name for this

testing is functional testing because it is only concerned with the testing of the

functionality and not the implementation of the software. This was done due to

the huge cost if the real scenario was to be done. The designer used this type

of testing on a downloaded sample data that is in the system and logically checks

the output to see if they conform with the system functionality.

6.3 Integration Testing

The whole programme was simulated to check if it functions according to the

requirements of the system.

6.4 User Interface Testing

As specified in the previous section of the project. The test was mainly conferred

on the existence of the user interface and its specification.

6.5 Output Testing

The system was able to produce the required output as specified in the section of

the output requirements of the system. When the user added the downloaded

fingerprints to the database and then select the option to authenticate, the

matching algorithm produced the desired results. The output testing was done

65

together with the processing testing as it can be seen that no system can

produce the required output using incorrect processes. Then it follows that

process testing was done successfully by the designated users.

The results which were simulated would be shown in the system out section.

After the execution of the system, the screen appears to control the users on

whatever information they need from the system. The demonstration will be

shown in the system output section. Then selecting the authentication option the

system invoke the pattern matching algorithm to authenticate the input fingerprint

with the fingerprint in the database.

On the same page all the options are available depending on the needs of the

user.

6.6 Walkthrough Testing

This was done on the system as a whole to make sure the integrated improved

security system conforms with the user requirements and functional

requirements. The type of testing is also used to check whether there are no

logical errors which are not dictated by the other testing methods. In this system

all the downloaded fingerprints including the spoofed were subjected to the

minutiae pattern matching algorithm.

66

6.7 Evaluation of the integrated improved security techniques

The time and space complexity were used to measure the performance and the

efficiency of the algorithm. The complexity had improved from n^2 t0 n.

67

CHAPTER 7:

CONCLUSIONS AND SUGGESTIONS FOR FUTURE WORK

7.1 Introduction

This chapter of the project covers the evaluation of the integrated improved

security system techniques to combat crime using the biometrics. Evaluation of

the system involves the discussion of the strength and the weaknesses

(limitations).

7.2 Evaluation

The research work satisfied its predefined objectives. The justification of the

appropriateness of the integrated improved security system techniques to

combat crime were ascertained after the simulation. Depending on the data

required by different users the system seems to work well giving accurate data

necessary for decision making purposes concerning the rate of crime. The

system however is not making on decision but it is giving data to the decision

makers on the concept of crime for them to make corporate decision.

7.3 Limitations

When the system is installed to any computer, a user with the knowledge of the

visual studio 2005 can open the database of results and view or change data

outside the application. The data is not very secure. In real world context,

network security and/or data encryption would be used to increase security.

68

Then in the world of this application, however, a visual studio user should have

access to the data.

Apart from the above system does not detect the spoofed fingerprints. The high

cost to set the real world is not feasible at the National Airport of Zimbabwe due

to hardware, software and application systems needed.

7.4 Suggested For Future Work

The issue of biometrics to fight crime is an issue these days. All the

stakeholders, creditors and other people are worried by the high and magnitude

of crimes which are prevalent these days. Furthermore the citizens are patiently

asking for the use of technology to improve the detection rate of the criminals.

Combating crime using biometrics have become an important research topic in

recent years, mostly because it produces interoperability, high performance and

efficiency. I suggest the former to be done using the three dimensional

coordinates. The fundamentals of the system remain the same but with

improved complexity and space.

Since the criminals are committing high profile cases the system would be used

to curb the phenomenon.

69

7.5 Recommendations

We recommend the continuous systematic and logical use of the integrated

improved security system techniques in combating crime using the biometrics.

70

CHAPTER 8

SYSTEM OUTPUT(SIMULATION , INTERFACE, COMPONENTS)

82

Imports System.IOImports SystemImports System.Collections

Public Class BIOMETRICS Dim cnt, cnt1, cnt2, pecnt, n As Integer Dim pathf, thestr, filestr As String Dim doq, dop As Boolean

Private Sub BtnExit_Click(ByVal sender As System.Object, ByVal e AsSystem.EventArgs) Handles BtnExit.Click End End Sub

Private Sub BtnAuthenticate_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles BtnAuthenticate.Click Dim sr As New StreamReader(pathf) PicFingerPrint.Left = 74 PicDataBase.Top = 176 PicResult.Left = 423 cnt = 0 cnt1 = 0 cnt2 = 0 doq = False dop = False TmrQ.Enabled = False TmrTemp.Enabled = False

TxtStringF.Text = sr.ReadToEnd

sr.Close() TmrAction.Enabled = True

End Sub

Private Sub TmrAction_Tick(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles TmrAction.Tick Dim palpha, plen, p As Integer TextBox1.Text = cnt cnt = cnt + 1 Select Case cnt Case 1 LblAction.Text = " Finger Print Scanner, Scanning Image" PicFingerPrint.Left = PicFingerPrint.Left + 12 Case 2 PicFingerPrint.Left = PicFingerPrint.Left + 12

Case 3 PicFingerPrint.Left = PicFingerPrint.Left + 12

Case 4 PicFingerPrint.Left = PicFingerPrint.Left + 12 LblAction.Text = " Finger Print Image" Case 5 PicFingerPrint.Left = PicFingerPrint.Left + 12

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Case 20 PicFingerPrint.Left = PicFingerPrint.Left + 12 Case 21 PicFingerPrint.Left = PicFingerPrint.Left + 12 Case 22 PicFingerPrint.Left = PicFingerPrint.Left + 12 Case 23 PicFingerPrint.Left = PicFingerPrint.Left + 12 Case 24 PicFingerPrint.Left = PicFingerPrint.Left + 12 Case 25 PicFingerPrint.Left = PicFingerPrint.Left + 12 LblAction.Text = " Minutia Extraction "

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Case 26 PicDataBase.Top = PicDataBase.Top + 12


Case 28 PicDataBase.Top = PicDataBase.Top + 12 LblAction.Text = "Minutia" Case 29 PicDataBase.Top = PicDataBase.Top + 12










Case 40 PicDataBase.Top = PicDataBase.Top + 12 LblAction.Text = "Minutia Matching" Case 41 PicDataBase.Top = PicDataBase.Top + 12

Case 42

Case 43 Case 44 Case 45 Case 46 Case 47 Case 48 Case 49 Case 50

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LblAction.Text = "Minutia Matching" & vbNewLine & vbNewLine & "1. Matching the ridge associated with each input minutia against the ridge asociated with each template minutia and align the two patterns according to the matching result" TmrTemp.Enabled = True plen = TxtStringF.TextLength For p = 0 To plen - 1 thestr = Strings.Mid(TxtStringF.Text, p + 1, 1) If thestr >= "0" And thestr <= "9" Then palpha = palpha + 1 End If If thestr >= "A" And thestr <= "Z" Then palpha = palpha + 1 End If If thestr >= "a" And thestr <= "z" Then palpha = palpha + 1 End If Next txtp.Text = palpha Case 51 Case 52 Case 53 Case 54 Case 55 Case 56 Case 57 Case 59 Case 60

LblAction.Text = "Minutia Matching" & vbNewLine & vbNewLine & "2. Convert the representation of template and input minutiate into the polar coodinate representation with respect to the corresponding minutia on which alignment is performed and represent them as two symbolic strings by concatenating each minuta in an increasing order of radial angles: " TmrTemp.Enabled = True TxtImg.Text = TxtStringF.TextLength / txtp.Text

Case 61 Case 62 Case 63 Case 64 Case 65 Case 66 Case 67 Case 68 txtq.Text = LstQ.Items.Item(0) TxtTemplate.Text = LstTempMin.Items.Item(0) Case 69 Case 70 LblAction.Text = "Minutia Matching" & vbNewLine & vbNewLine & "3. Matching the resulting strings Pp and Qq with a modified dynamic-programming algorithm decribed below to find the 'edit distance' between Pp and Qq." TmrTemp.Enabled = True

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Case 71 TmrQ.Enabled = True Case 72 Case 73 Case 74 Case 75 Case 76 Case 77 Case 78 Case 79 Case 80 LblAction.Text = "Minutia Matching" & vbNewLine & vbNewLine & "4. Compute the matching score of the template and input minutiae a the minimum 'edit distance'." & vbNewLine & "The max and min values of the matching score are 100 and 1, respectively. The former value indicates a perfect match, while the later value indicates no match at all." TmrTemp.Enabled = True If TxtImg.Text >= TxtTemplate.Text Then txtMatching.Text = (100 * TxtTemplate.Text ^ 2) / (TxtImg.Text ^ 2) Else txtMatching.Text = (100 * TxtImg.Text ^ 2) / (TxtTemplate.Text ^ 2) End If

Case 81 If txtMatching.Text > pecnt Then TxtToReport.Text = TxtToReport.Text & vbNewLine & LstTempMin.Items.Count & vbTab & " | " & vbTab & "CORRECT" & vbTab & "|" & vbTab & Strings.FormatNumber(txtMatching.Text, 3) Else TxtToReport.Text = TxtToReport.Text & vbNewLine & LstTempMin.Items.Count & vbTab & " | " & vbTab & Strings.FormatNumber(txtMatching.Text, 3) & vbTab & vbTab & "|" & vbTab & "INCORRECT" End If Txtexcel.Text = Txtexcel.Text & vbNewLine & LstTempMin.Items.Count & vbTab & Strings.FormatNumber(txtMatching.Text, 3) & vbTab & txtq.Text & vbTab & txtp.Text & vbTab & TxtTemplate.Text

TmrAction.Interval = 100 PicResult.Left = PicResult.Left + 12 Case 82 PicResult.Left = PicResult.Left + 12

Case 83 PicResult.Left = PicResult.Left + 12



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Case 105

Case 106

cnt = 0 TmrAction.Enabled = False

End Select

If cnt > 90 Then

If txtMatching.Text <= pecnt Then PicResult.Visible = False PicNo.Visible = True Else PicResult.Visible = True PicNo.Visible = False End If PicNo.Left = PicResult.Left End If

If cnt >= 106 Then TmrAction.Enabled = False cnt = 0 End If End Sub

Private Sub BtnBrowesPrint_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles BtnBrowesPrint.Click 'TmrAction.Enabled = True OpenFileDialog1.InitialDirectory = "BIOMETRICS" 'OpenFileDialog1.ShowDialog() If OpenFileDialog1.ShowDialog = Windows.Forms.DialogResult.OK Then LstFingerP.Items.Add(My.Computer.FileSystem.GetName(OpenFileDialog1.FileName)) LstPath.Items.Add(OpenFileDialog1.FileName) End If

End Sub

Private Sub BIOMETRICS_Load(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles MyBase.Load For n = 0 To 100 ComboBox1.Items.Add(n) Next ComboBox1.SelectedIndex = 75 TxtToReport.Text = "" TxtToReport.Text = TxtToReport.Text & vbTab & vbTab & "Normalised Matching Score" & vbNewLine & "----------------------------------------------------------------------------------------------"

TxtToReport.Text = TxtToReport.Text & vbNewLine & "DB size" & vbTab & " | " & vbTab & "INCORRECT" & vbTab & "|" & vbTab & "CORRECT"

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TxtToReport.Text = TxtToReport.Text & vbNewLine & "_______________________________________________________"

End Sub

Private Sub PicComputer_Click(ByVal sender As System.Object, ByVale As System.EventArgs)

End Sub

Private Sub OpenFileDialog1_FileOk(ByVal sender As System.Object, ByVal e As System.ComponentModel.CancelEventArgs) HandlesOpenFileDialog1.FileOk

End Sub

Private Sub TmrTemp_Tick(ByVal sender As System.Object, ByVal e AsSystem.EventArgs) Handles TmrTemp.Tick cnt1 = cnt1 + 1 Select Case cnt1

Case 1

Case 2 PicTemp.BackgroundImage = ImageList1.Images.Item(cnt1)











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Case 18

Case 19

Case 20 cnt1 = 0 TmrTemp.Enabled = False End Select End Sub

Private Sub BtnReport_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles BtnReport.Click Dim rd As New StreamReader("C:\BIOMETRICS\BIOMETRICS.xls") filestr = rd.ReadToEnd rd.Close() writetofile() Process.Start("C:\BIOMETRICS\BIOMETRICS.xls")

End Sub

Public Sub writetofile()

Dim sw As New StreamWriter("C:\BIOMETRICS\BIOMETRICS.xls") sw.WriteLine(filestr & Txtexcel.Text) sw.Close()

End Sub

Private Sub LstFingerP_SelectedIndexChanged(ByVal sender AsSystem.Object, ByVal e As System.EventArgs) HandlesLstFingerP.SelectedIndexChanged If LstFingerP.SelectedIndex >= 0 Then pathf = LstPath.Items.Item(LstFingerP.SelectedIndex) End If End Sub

Private Sub Button2_Click(ByVal sender As System.Object, ByVal e AsSystem.EventArgs) Handles Button2.Click

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LstTempMin.Items.RemoveAt(LstTempMin.SelectedIndex) LstQ.Items.RemoveAt(LstQ.SelectedIndex)

End Sub

Private Sub Button1_Click(ByVal sender As System.Object, ByVal e AsSystem.EventArgs) Handles Button1.Click

Dim adtemp, PLEN, P, PALPHA As Integer

Dim sr1 As New StreamReader(pathf)

TxtStringF.Text = sr1.ReadToEnd

sr1.Close()

PLEN = TxtStringF.TextLength For P = 0 To TxtStringF.TextLength - 1

thestr = Strings.Mid(TxtStringF.Text, P + 1, 1) If thestr >= "0" And thestr <= "9" Then PALPHA = PALPHA + 1 End If If thestr >= "A" And thestr <= "Z" Then PALPHA = PALPHA + 1 End If If thestr >= "a" And thestr <= "z" Then PALPHA = PALPHA + 1 End If

Next If PALPHA > 0 Then adtemp = TxtStringF.TextLength / PALPHA

End If

LstQ.Items.Add(PALPHA) LstTempMin.Items.Add(adtemp) End Sub

Private Sub TmrQ_Tick(ByVal sender As System.Object, ByVal e AsSystem.EventArgs) Handles TmrQ.Tick Dim temp As Integer

If cnt2 >= LstQ.Items.Count - 1 Then TmrQ.Enabled = False 'cnt2 = 0 End If LstQ.SelectedIndex = cnt2 LstTempMin.SelectedIndex = cnt2

For temp = cnt2 To LstQ.Items.Count - 1

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If txtq.Text / LstQ.Items.Item(cnt2) > txtq.Text / LstQ.Items.Item(temp) Then txtq.Text = LstQ.Items.Item(cnt2) TxtTemplate.Text = LstTempMin.Items.Item(cnt2) ElseIf txtq.Text / LstQ.Items.Item(cnt2) < txtq.Text / LstQ.Items.Item(temp) Then txtq.Text = LstQ.Items.Item(temp) TxtTemplate.Text = LstTempMin.Items.Item(temp) End If

Next

If txtq.Text = txtp.Text Then TmrQ.Enabled = False TmrTemp.Enabled = False ' cnt2 = 0 End If

cnt2 = cnt2 + 1

End Sub

Private Sub Tmrtemplate_Tick(ByVal sender As System.Object, ByVal e As System.EventArgs)

End Sub

Private Sub ComboBox1_SelectedIndexChanged(ByVal sender AsSystem.Object, ByVal e As System.EventArgs) HandlesComboBox1.SelectedIndexChanged pecnt = ComboBox1.Text End SubEnd Class

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<Global.Microsoft.VisualBasic.CompilerServices.DesignerGenerated()> _Partial Class BIOMETRICS Inherits System.Windows.Forms.Form

'Form overrides dispose to clean up the component list. <System.Diagnostics.DebuggerNonUserCode()> _ Protected Overrides Sub Dispose(ByVal disposing As Boolean) If disposing AndAlso components IsNot Nothing Then components.Dispose() End If MyBase.Dispose(disposing) End Sub

'Required by the Windows Form Designer Private components As System.ComponentModel.IContainer

'NOTE: The following procedure is required by the Windows Form Designer 'It can be modified using the Windows Form Designer. 'Do not modify it using the code editor. <System.Diagnostics.DebuggerStepThrough()> _ Private Sub InitializeComponent() Me.components = New System.ComponentModel.Container Dim resources As System.ComponentModel.ComponentResourceManager = NewSystem.ComponentModel.ComponentResourceManager(GetType(BIOMETRICS)) Me.Label1 = New System.Windows.Forms.Label Me.GroupBox1 = New System.Windows.Forms.GroupBox Me.BtnExit = New System.Windows.Forms.Button Me.BtnReport = New System.Windows.Forms.Button

Me.BtnAuthenticate = New System.Windows.Forms.Button Me.BtnBrowesPrint = New System.Windows.Forms.Button Me.TmrAction = New System.Windows.Forms.Timer(Me.components) Me.OpenFileDialog1 = New System.Windows.Forms.OpenFileDialog Me.LblAction = New System.Windows.Forms.Label Me.GroupBox2 = New System.Windows.Forms.GroupBox Me.Label3 = New System.Windows.Forms.Label Me.Label6 = New System.Windows.Forms.Label Me.txtMatching = New System.Windows.Forms.TextBox Me.Label5 = New System.Windows.Forms.Label Me.TxtTemplate = New System.Windows.Forms.TextBox Me.Label4 = New System.Windows.Forms.Label Me.Label2 = New System.Windows.Forms.Label Me.TxtImg = New System.Windows.Forms.TextBox Me.txtq = New System.Windows.Forms.TextBox Me.txtp = New System.Windows.Forms.TextBox Me.LstFingerP = New System.Windows.Forms.ListBox Me.ImageList1 = NewSystem.Windows.Forms.ImageList(Me.components) Me.TmrTemp = New System.Windows.Forms.Timer(Me.components) Me.TxtToReport = New System.Windows.Forms.TextBox Me.TxtStringF = New System.Windows.Forms.TextBox Me.LstTempMin = New System.Windows.Forms.ListBox Me.Button1 = New System.Windows.Forms.Button Me.Button2 = New System.Windows.Forms.Button Me.LstQ = New System.Windows.Forms.ListBox Me.PicNo = New System.Windows.Forms.PictureBox

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Me.PicTemp = New System.Windows.Forms.PictureBox Me.PicServer = New System.Windows.Forms.PictureBox Me.PictureBox1 = New System.Windows.Forms.PictureBox Me.PicDB = New System.Windows.Forms.PictureBox Me.PicResult = New System.Windows.Forms.PictureBox Me.PicDataBase = New System.Windows.Forms.PictureBox Me.PicFingerPrint = New System.Windows.Forms.PictureBox Me.PicComputer = New System.Windows.Forms.PictureBox Me.TmrQ = New System.Windows.Forms.Timer(Me.components) Me.LstPath = New System.Windows.Forms.ListBox Me.TextBox1 = New System.Windows.Forms.TextBox Me.ComboBox1 = New System.Windows.Forms.ComboBox Me.Txtexcel = New System.Windows.Forms.TextBox Me.GroupBox1.SuspendLayout() Me.GroupBox2.SuspendLayout() CType(Me.PicNo, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PicTemp, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PicServer, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PictureBox1, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PicDB, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PicResult, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PicDataBase, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PicFingerPrint, System.ComponentModel.ISupportInitialize).BeginInit() CType(Me.PicComputer, System.ComponentModel.ISupportInitialize).BeginInit() Me.SuspendLayout() ' 'Label1 ' Me.Label1.AutoSize = True Me.Label1.Location = New System.Drawing.Point(37, 426) Me.Label1.Name = "Label1" Me.Label1.Size = New System.Drawing.Size(98, 13) Me.Label1.TabIndex = 4 Me.Label1.Text = "Finger Print Reader" ' 'GroupBox1 ' Me.GroupBox1.Controls.Add(Me.BtnExit) Me.GroupBox1.Controls.Add(Me.BtnReport) Me.GroupBox1.Controls.Add(Me.BtnAuthenticate) Me.GroupBox1.Controls.Add(Me.BtnBrowesPrint) Me.GroupBox1.Location = New System.Drawing.Point(12, 607) Me.GroupBox1.Name = "GroupBox1" Me.GroupBox1.Size = New System.Drawing.Size(947, 80) Me.GroupBox1.TabIndex = 6 Me.GroupBox1.TabStop = False ' 'BtnExit

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' Me.BtnExit.Font = New System.Drawing.Font("Microsoft Sans Serif", 12.0!, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.BtnExit.Location = New System.Drawing.Point(788, 19) Me.BtnExit.Name = "BtnExit" Me.BtnExit.Size = New System.Drawing.Size(126, 44) Me.BtnExit.TabIndex = 3 Me.BtnExit.Text = "Exit" Me.BtnExit.UseVisualStyleBackColor = True ' 'BtnReport ' Me.BtnReport.Font = New System.Drawing.Font("Microsoft Sans Serif", 12.0!, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.BtnReport.Location = New System.Drawing.Point(555, 18) Me.BtnReport.Name = "BtnReport" Me.BtnReport.Size = New System.Drawing.Size(126, 44) Me.BtnReport.TabIndex = 2 Me.BtnReport.Text = "View Report" Me.BtnReport.UseVisualStyleBackColor = True ' 'BtnAuthenticate ' Me.BtnAuthenticate.Font = New System.Drawing.Font("Microsoft Sans Serif", 12.0!, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.BtnAuthenticate.Location = New System.Drawing.Point(298, 18) Me.BtnAuthenticate.Name = "BtnAuthenticate" Me.BtnAuthenticate.Size = New System.Drawing.Size(126, 44) Me.BtnAuthenticate.TabIndex = 1 Me.BtnAuthenticate.Text = "Authenticate" Me.BtnAuthenticate.UseVisualStyleBackColor = True ' 'BtnBrowesPrint ' Me.BtnBrowesPrint.Font = New System.Drawing.Font("Microsoft Sans Serif", 12.0!, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.BtnBrowesPrint.Location = New System.Drawing.Point(34, 19) Me.BtnBrowesPrint.Name = "BtnBrowesPrint" Me.BtnBrowesPrint.Size = New System.Drawing.Size(126, 44) Me.BtnBrowesPrint.TabIndex = 0 Me.BtnBrowesPrint.Text = "Finger Print" Me.BtnBrowesPrint.UseVisualStyleBackColor = True ' 'TmrAction ' Me.TmrAction.Interval = 450 ' 'OpenFileDialog1 ' Me.OpenFileDialog1.FileName = "OpenFileDialog1" ' 'LblAction '

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Me.LblAction.BorderStyle = System.Windows.Forms.BorderStyle.FixedSingle Me.LblAction.FlatStyle = System.Windows.Forms.FlatStyle.Popup Me.LblAction.Font = New System.Drawing.Font("Times New Roman", 12.0!, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.LblAction.Location = New System.Drawing.Point(-2, 9) Me.LblAction.Name = "LblAction" Me.LblAction.Size = New System.Drawing.Size(983, 101) Me.LblAction.TabIndex = 8 ' 'GroupBox2 ' Me.GroupBox2.Controls.Add(Me.Label3) Me.GroupBox2.Controls.Add(Me.Label6) Me.GroupBox2.Controls.Add(Me.txtMatching) Me.GroupBox2.Controls.Add(Me.Label5) Me.GroupBox2.Controls.Add(Me.TxtTemplate) Me.GroupBox2.Controls.Add(Me.Label4) Me.GroupBox2.Controls.Add(Me.Label2) Me.GroupBox2.Controls.Add(Me.TxtImg) Me.GroupBox2.Controls.Add(Me.txtq) Me.GroupBox2.Controls.Add(Me.txtp) Me.GroupBox2.Location = New System.Drawing.Point(321, 436) Me.GroupBox2.Name = "GroupBox2" Me.GroupBox2.Size = New System.Drawing.Size(222, 156) Me.GroupBox2.TabIndex = 23 Me.GroupBox2.TabStop = False ' 'Label3 ' Me.Label3.AutoSize = True Me.Label3.Font = New System.Drawing.Font("Microsoft Sans Serif", 8.25!, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.Label3.Location = New System.Drawing.Point(2, 41) Me.Label3.Name = "Label3" Me.Label3.Size = New System.Drawing.Size(135, 13) Me.Label3.TabIndex = 33 Me.Label3.Text = "Polar Coordinates (Qq)" ' 'Label6

' Me.Label6.AutoSize = True Me.Label6.Font = New System.Drawing.Font("Microsoft Sans Serif", 9.75!, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.Label6.Location = New System.Drawing.Point(2, 133) Me.Label6.Name = "Label6" Me.Label6.Size = New System.Drawing.Size(115, 16) Me.Label6.TabIndex = 32 Me.Label6.Text = "Matching Score" ' 'txtMatching ' Me.txtMatching.BackColor = System.Drawing.Color.Silver

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Me.txtMatching.Font = New System.Drawing.Font("Microsoft Sans Serif", 9.75!, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.txtMatching.Location = New System.Drawing.Point(151, 127) Me.txtMatching.Name = "txtMatching" Me.txtMatching.Size = New System.Drawing.Size(64, 22) Me.txtMatching.TabIndex = 31 ' 'Label5 ' Me.Label5.AutoSize = True Me.Label5.Font = New System.Drawing.Font("Microsoft Sans Serif", 8.25!, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.Label5.Location = New System.Drawing.Point(2, 97) Me.Label5.Name = "Label5" Me.Label5.Size = New System.Drawing.Size(88, 13) Me.Label5.TabIndex = 30 Me.Label5.Text = "Input Minutiae" ' 'TxtTemplate ' Me.TxtTemplate.Location = New System.Drawing.Point(130, 72) Me.TxtTemplate.Name = "TxtTemplate" Me.TxtTemplate.Size = New System.Drawing.Size(85, 20) Me.TxtTemplate.TabIndex = 29 ' 'Label4 ' Me.Label4.AutoSize = True Me.Label4.Font = New System.Drawing.Font("Microsoft Sans Serif", 8.25!, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.Label4.Location = New System.Drawing.Point(2, 75) Me.Label4.Name = "Label4" Me.Label4.Size = New System.Drawing.Size(111, 13) Me.Label4.TabIndex = 28 Me.Label4.Text = "Template Minutiae" ' 'Label2 ' Me.Label2.AutoSize = True Me.Label2.Font = New System.Drawing.Font("Microsoft Sans Serif", 8.25!, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, CType(0, Byte)) Me.Label2.Location = New System.Drawing.Point(2, 19) Me.Label2.Name = "Label2" Me.Label2.Size = New System.Drawing.Size(134, 13) Me.Label2.TabIndex = 26 Me.Label2.Text = "Polar Coordinates (Pq)" ' 'TxtImg ' Me.TxtImg.Location = New System.Drawing.Point(130, 94) Me.TxtImg.Name = "TxtImg" Me.TxtImg.Size = New System.Drawing.Size(85, 20) Me.TxtImg.TabIndex = 25

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' 'txtq ' Me.txtq.Location = New System.Drawing.Point(142, 16) Me.txtq.Name = "txtq" Me.txtq.Size = New System.Drawing.Size(73, 20) Me.txtq.TabIndex = 24 ' 'txtp ' Me.txtp.Location = New System.Drawing.Point(142, 38) Me.txtp.Name = "txtp" Me.txtp.Size = New System.Drawing.Size(73, 20) Me.txtp.TabIndex = 23 ' 'LstFingerP ' Me.LstFingerP.FormattingEnabled = True Me.LstFingerP.HorizontalScrollbar = True Me.LstFingerP.Location = New System.Drawing.Point(31, 447) Me.LstFingerP.Name = "LstFingerP" Me.LstFingerP.Size = New System.Drawing.Size(119, 134) Me.LstFingerP.TabIndex = 27 ' 'ImageList1 ' Me.ImageList1.ImageStream = CType(resources.GetObject("ImageList1.ImageStream"), System.Windows.Forms.ImageListStreamer) Me.ImageList1.TransparentColor = System.Drawing.Color.Transparent Me.ImageList1.Images.SetKeyName(0, "f1.jpeg") Me.ImageList1.Images.SetKeyName(1, "fp1.jpeg") Me.ImageList1.Images.SetKeyName(2, "fp2.jpeg") Me.ImageList1.Images.SetKeyName(3, "fp4.jpeg") Me.ImageList1.Images.SetKeyName(4, "fp5.jpeg") Me.ImageList1.Images.SetKeyName(5, "fp6.jpeg") Me.ImageList1.Images.SetKeyName(6, "fp7.jpeg") Me.ImageList1.Images.SetKeyName(7, "fp8.jpeg") Me.ImageList1.Images.SetKeyName(8, "fp10.jpeg") Me.ImageList1.Images.SetKeyName(9, "fp11.jpeg") Me.ImageList1.Images.SetKeyName(10, "fp12.jpeg")

Me.ImageList1.Images.SetKeyName(11, "fp13.jpeg") Me.ImageList1.Images.SetKeyName(12, "fp14.jpeg") Me.ImageList1.Images.SetKeyName(13, "fp15.jpeg") Me.ImageList1.Images.SetKeyName(14, "fpr1.jpeg") Me.ImageList1.Images.SetKeyName(15, "fpr3.jpeg") Me.ImageList1.Images.SetKeyName(16, "fpr5.jpeg") Me.ImageList1.Images.SetKeyName(17, "fpr2.jpeg") ' 'TmrTemp ' Me.TmrTemp.Interval = 4000 ' 'TxtToReport ' Me.TxtToReport.BackColor = System.Drawing.Color.DarkGray

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Me.TxtToReport.Location = New System.Drawing.Point(626, 445) Me.TxtToReport.Multiline = True Me.TxtToReport.Name = "TxtToReport" Me.TxtToReport.ScrollBars = System.Windows.Forms.ScrollBars.Both Me.TxtToReport.Size = New System.Drawing.Size(333, 156) Me.TxtToReport.TabIndex = 28 Me.TxtToReport.Text = "Normalised Matching Score" & Global.Microsoft.VisualBasic.ChrW(13) & Global.Microsoft.VisualBasic.ChrW(10) & "-----------------------------------------------" & Global.Microsoft.VisualBasic.ChrW(13) & Global.Microsoft.VisualBasic.ChrW(10) & Global.Microsoft.VisualBasic.ChrW(13) & Global.Microsoft.VisualBasic.ChrW(10) & "DB " & _ "size | Correct | InCorrect" & Global.Microsoft.VisualBasic.ChrW(13) & Global.Microsoft.VisualBasic.ChrW(10) & "________________________________" & Global.Microsoft.VisualBasic.ChrW(13) & Global.Microsoft.VisualBasic.ChrW(10) & _ "" & Global.Microsoft.VisualBasic.ChrW(13) & Global.Microsoft.VisualBasic.ChrW(10) ' 'TxtStringF ' Me.TxtStringF.Location = New System.Drawing.Point(-2, 113) Me.TxtStringF.Multiline = True Me.TxtStringF.Name = "TxtStringF" Me.TxtStringF.Size = New System.Drawing.Size(214, 61) Me.TxtStringF.TabIndex = 29 ' 'LstTempMin ' Me.LstTempMin.FormattingEnabled = True Me.LstTempMin.Location = New System.Drawing.Point(678, 113) Me.LstTempMin.Name = "LstTempMin" Me.LstTempMin.Size = New System.Drawing.Size(51, 69) Me.LstTempMin.TabIndex = 30 ' 'Button1 ' Me.Button1.Location = New System.Drawing.Point(786, 113) Me.Button1.Name = "Button1" Me.Button1.Size = New System.Drawing.Size(117, 30) Me.Button1.TabIndex = 31 Me.Button1.Text = "Add New" Me.Button1.UseVisualStyleBackColor = True ' 'Button2 ' Me.Button2.Location = New System.Drawing.Point(786, 149) Me.Button2.Name = "Button2" Me.Button2.Size = New System.Drawing.Size(117, 30) Me.Button2.TabIndex = 32 Me.Button2.Text = "Remove" Me.Button2.UseVisualStyleBackColor = True '

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'LstQ ' Me.LstQ.FormattingEnabled = True Me.LstQ.Location = New System.Drawing.Point(735, 113) Me.LstQ.Name = "LstQ" Me.LstQ.Size = New System.Drawing.Size(45, 69) Me.LstQ.TabIndex = 33 ' 'PicNo ' Me.PicNo.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.fileIcon1 Me.PicNo.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicNo.Location = New System.Drawing.Point(427, 388) Me.PicNo.Name = "PicNo" Me.PicNo.Size = New System.Drawing.Size(31, 26) Me.PicNo.TabIndex = 34 Me.PicNo.TabStop = False ' 'PicTemp ' Me.PicTemp.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicTemp.Location = New System.Drawing.Point(472, 113) Me.PicTemp.Name = "PicTemp" Me.PicTemp.Size = New System.Drawing.Size(77, 106) Me.PicTemp.TabIndex = 25

Me.PicTemp.TabStop = False ' 'PicServer ' Me.PicServer.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.server2 Me.PicServer.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicServer.Location = New System.Drawing.Point(678, 188) Me.PicServer.Name = "PicServer" Me.PicServer.Size = New System.Drawing.Size(225, 251) Me.PicServer.TabIndex = 24 Me.PicServer.TabStop = False ' 'PictureBox1 ' Me.PictureBox1.BackColor = System.Drawing.SystemColors.AppWorkspace Me.PictureBox1.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.fpreader2 Me.PictureBox1.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PictureBox1.Location = New System.Drawing.Point(40, 296) Me.PictureBox1.Name = "PictureBox1" Me.PictureBox1.Size = New System.Drawing.Size(113, 118) Me.PictureBox1.TabIndex = 12 Me.PictureBox1.TabStop = False ' 'PicDB

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' Me.PicDB.BackColor = System.Drawing.SystemColors.ActiveCaption Me.PicDB.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.db1 Me.PicDB.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicDB.Location = New System.Drawing.Point(381, 113) Me.PicDB.Name = "PicDB" Me.PicDB.Size = New System.Drawing.Size(93, 106) Me.PicDB.TabIndex = 11 Me.PicDB.TabStop = False ' 'PicResult ' Me.PicResult.BackColor = System.Drawing.SystemColors.ActiveCaption Me.PicResult.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.cor Me.PicResult.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicResult.Location = New System.Drawing.Point(423, 395) Me.PicResult.Name = "PicResult" Me.PicResult.Size = New System.Drawing.Size(35, 35) Me.PicResult.TabIndex = 9 Me.PicResult.TabStop = False ' 'PicDataBase ' Me.PicDataBase.BackColor = System.Drawing.SystemColors.ActiveCaption Me.PicDataBase.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.fileIcon Me.PicDataBase.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicDataBase.Location = New System.Drawing.Point(411, 176) Me.PicDataBase.Name = "PicDataBase" Me.PicDataBase.Size = New System.Drawing.Size(32, 29) Me.PicDataBase.TabIndex = 7 Me.PicDataBase.TabStop = False ' 'PicFingerPrint ' Me.PicFingerPrint.BackColor = System.Drawing.SystemColors.AppWorkspace Me.PicFingerPrint.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.fp2 Me.PicFingerPrint.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicFingerPrint.Location = New System.Drawing.Point(74, 328) Me.PicFingerPrint.Name = "PicFingerPrint" Me.PicFingerPrint.Size = New System.Drawing.Size(50, 75) Me.PicFingerPrint.TabIndex = 5 Me.PicFingerPrint.TabStop = False ' 'PicComputer '

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Me.PicComputer.BackColor = System.Drawing.SystemColors.AppWorkspace Me.PicComputer.BackgroundImage = Global.BIOMETRICS.My.Resources.Resources.comp1 Me.PicComputer.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.PicComputer.Location = New System.Drawing.Point(359, 328) Me.PicComputer.Name = "PicComputer" Me.PicComputer.Size = New System.Drawing.Size(136, 111) Me.PicComputer.TabIndex = 35 Me.PicComputer.TabStop = False ' 'TmrQ ' ' 'LstPath ' Me.LstPath.FormattingEnabled = True Me.LstPath.HorizontalScrollbar = True Me.LstPath.Location = New System.Drawing.Point(156, 447) Me.LstPath.Name = "LstPath" Me.LstPath.Size = New System.Drawing.Size(119, 134) Me.LstPath.TabIndex = 36 Me.LstPath.Visible = False ' 'TextBox1 ' Me.TextBox1.Location = New System.Drawing.Point(888, 426) Me.TextBox1.Name = "TextBox1" Me.TextBox1.Size = New System.Drawing.Size(71, 20) Me.TextBox1.TabIndex = 37 ' 'ComboBox1 ' Me.ComboBox1.FormattingEnabled = True Me.ComboBox1.Location = New System.Drawing.Point(359, 310) Me.ComboBox1.Name = "ComboBox1" Me.ComboBox1.Size = New System.Drawing.Size(136, 21) Me.ComboBox1.TabIndex = 38 ' 'Txtexcel ' Me.Txtexcel.BackColor = System.Drawing.Color.DarkGray Me.Txtexcel.Location = New System.Drawing.Point(31, 587) Me.Txtexcel.Multiline = True Me.Txtexcel.Name = "Txtexcel" Me.Txtexcel.ScrollBars = System.Windows.Forms.ScrollBars.Both Me.Txtexcel.Size = New System.Drawing.Size(244, 22) Me.Txtexcel.TabIndex = 39 Me.Txtexcel.Visible = False ' 'BIOMETRICS ' Me.AutoScaleDimensions = New System.Drawing.SizeF(6.0!, 13.0!) Me.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font Me.BackColor = System.Drawing.Color.White

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Me.BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch Me.ClientSize = New System.Drawing.Size(971, 681) Me.ControlBox = False Me.Controls.Add(Me.Txtexcel) Me.Controls.Add(Me.ComboBox1) Me.Controls.Add(Me.TextBox1) Me.Controls.Add(Me.LstPath) Me.Controls.Add(Me.PicComputer) Me.Controls.Add(Me.PicNo) Me.Controls.Add(Me.LstQ) Me.Controls.Add(Me.Button2) Me.Controls.Add(Me.Button1) Me.Controls.Add(Me.LstTempMin) Me.Controls.Add(Me.TxtStringF) Me.Controls.Add(Me.TxtToReport) Me.Controls.Add(Me.LstFingerP) Me.Controls.Add(Me.PicTemp) Me.Controls.Add(Me.PicServer) Me.Controls.Add(Me.GroupBox2) Me.Controls.Add(Me.PictureBox1) Me.Controls.Add(Me.PicDB) Me.Controls.Add(Me.PicResult) Me.Controls.Add(Me.LblAction) Me.Controls.Add(Me.PicDataBase) Me.Controls.Add(Me.GroupBox1) Me.Controls.Add(Me.PicFingerPrint) Me.Controls.Add(Me.Label1) Me.Name = "BIOMETRICS" Me.StartPosition = System.Windows.Forms.FormStartPosition.CenterScreen Me.Text = "MWARI PINDIRAI" Me.GroupBox1.ResumeLayout(False) Me.GroupBox2.ResumeLayout(False) Me.GroupBox2.PerformLayout() CType(Me.PicNo, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PicTemp, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PicServer, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PictureBox1, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PicDB, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PicResult, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PicDataBase, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PicFingerPrint, System.ComponentModel.ISupportInitialize).EndInit() CType(Me.PicComputer, System.ComponentModel.ISupportInitialize).EndInit() Me.ResumeLayout(False) Me.PerformLayout()

End Sub

104

Friend WithEvents Label1 As System.Windows.Forms.Label Friend WithEvents PicFingerPrint As System.Windows.Forms.PictureBox Friend WithEvents GroupBox1 As System.Windows.Forms.GroupBox Friend WithEvents BtnExit As System.Windows.Forms.Button Friend WithEvents BtnReport As System.Windows.Forms.Button Friend WithEvents BtnAuthenticate As System.Windows.Forms.Button Friend WithEvents BtnBrowesPrint As System.Windows.Forms.Button Friend WithEvents PicDataBase As System.Windows.Forms.PictureBox Friend WithEvents TmrAction As System.Windows.Forms.Timer Friend WithEvents OpenFileDialog1 AsSystem.Windows.Forms.OpenFileDialog Friend WithEvents LblAction As System.Windows.Forms.Label Friend WithEvents PicResult As System.Windows.Forms.PictureBox Friend WithEvents PicDB As System.Windows.Forms.PictureBox Friend WithEvents PictureBox1 As System.Windows.Forms.PictureBox Friend WithEvents GroupBox2 As System.Windows.Forms.GroupBox Friend WithEvents Label6 As System.Windows.Forms.Label Friend WithEvents txtMatching As System.Windows.Forms.TextBox Friend WithEvents Label5 As System.Windows.Forms.Label Friend WithEvents TxtTemplate As System.Windows.Forms.TextBox Friend WithEvents Label4 As System.Windows.Forms.Label Friend WithEvents Label2 As System.Windows.Forms.Label Friend WithEvents TxtImg As System.Windows.Forms.TextBox Friend WithEvents txtq As System.Windows.Forms.TextBox Friend WithEvents txtp As System.Windows.Forms.TextBox Friend WithEvents Label3 As System.Windows.Forms.Label Friend WithEvents PicServer As System.Windows.Forms.PictureBox Friend WithEvents PicTemp As System.Windows.Forms.PictureBox Friend WithEvents LstFingerP As System.Windows.Forms.ListBox Friend WithEvents ImageList1 As System.Windows.Forms.ImageList Friend WithEvents TmrTemp As System.Windows.Forms.Timer Friend WithEvents TxtToReport As System.Windows.Forms.TextBox Friend WithEvents TxtStringF As System.Windows.Forms.TextBox Friend WithEvents LstTempMin As System.Windows.Forms.ListBox Friend WithEvents Button1 As System.Windows.Forms.Button Friend WithEvents Button2 As System.Windows.Forms.Button Friend WithEvents LstQ As System.Windows.Forms.ListBox Friend WithEvents PicNo As System.Windows.Forms.PictureBox Friend WithEvents PicComputer As System.Windows.Forms.PictureBox Friend WithEvents TmrQ As System.Windows.Forms.Timer Friend WithEvents LstPath As System.Windows.Forms.ListBox Friend WithEvents TextBox1 As System.Windows.Forms.TextBox Friend WithEvents ComboBox1 As System.Windows.Forms.ComboBox Friend WithEvents Txtexcel As System.Windows.Forms.TextBox

End Class

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Sithole Thesis - UNIVERSITY OF ZIMBABWE

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