BIOMETRIC SYSTEM BASED ON FACE RECOGNITION SYSTEM Suad Hajı Ahmed Omar Master ...

59 Pages·2016·1.86 MB·English

BIOMETRIC SYSTEM BASED ON
FACE RECOGNITION SYSTEM

Suad Hajı Ahmed Omar
Master Thesis
Department of Software Engineering
Supervisor: Prof. Dr. Asaf VAROL

June-2016
REPUBLIC OF TURKEY
FIRAT UNIVERSITY
THE INSTITUTE OF NATURAL AND APPLIED SCIENCES

BIOMETRIC SYSTEM BASED ON FACE RECOGNITION SYSTEM

MASTER THESIS

Suad Haji Ahmed Omar

(141137102)

Thesis Submitted Date: 05 May 2016
Thesis Defense Date: 02 June 2016

Supervisor: Prof. Dr. Asaf VAROL (F.Ü.)
Other members of the jury: Assoc.Prof. Dr. M. Fatih TALU (I.U.)
Asst. Prof. Dr.Mustafa ULAŞ (F.U.)

June - 2016
DECLARATION
I am presenting this thesis with title “Biometric System Based on
Face Recognition System” for the requirement of Master’s degree in Software Engineering. I
declare that proposed system in thesis is my own work with all simulations and programming.

Suad Haji
Elazig, 2016

I
DEDICATION
This thesis is dedicated to my wonderful mother for her love and measureless support and my
husband and my older sister for their greatest influence on my life.

II
ACKNOWLEDGEMENTS
I want to thank all the staff members of Department of Software Engineering at Firat University,
without their help it would be impossible for me to complete my study of Master Degree. It was
my first time in my life to stay outside of my own country for as long but the love and care of all
staff members including staff of my hostel never let me to feel any difference. Prof. Dr. Asaf
VAROL was not only chairman of my department, he was also supervisor for my thesis. During
the study he helped me more than a chairman and teacher. Words cannot pay back anyone’s
kindness and help but still I want to say thanks to all.
Secondly, I would like to thanks to the department members of Software Engineering for their
significant helps and feedback as well as for accepting my thesis and continued to encourage me,
I learned a lot from them.
Lastly, I would like to express my sincerest gratitude to my parents for their supports and
encouragement throughout my studies. This studies would not have been possible without support
of my wonderful mother, sisters, my husband, and brother’s, thanks for their support and
companionship.

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TABLE OF CONTENTS
Page No
DECLARATION........................................................................................................................ I
DEDICATION.......................................................................................................................... II
ACKNOWLEDGEMENTS ................................................................................................... III
TABLE OF CONTENTS ....................................................................................................... IV
ABSTRACT ........................................................................................................................... VII
LIST OF FIGURES ............................................................................................................. VIII
LIST OF TABLES .................................................................................................................. IX
ABBREVIATIONS .................................................................................................................. X
1. INTRODUCTION ................................................................................................................ 1
1.1. Statement of the Problem ................................................................................................ 1
1.2. Project Overview ............................................................................................................. 2
1.3. Scope and Limitation ...................................................................................................... 2
2. BIOMETRICS ...................................................................................................................... 3
2.1. Overview ......................................................................................................................... 3
2.2. Types of Biometrics ........................................................................................................ 4
2.2.1. Behaviometrics (behavioral biometrics) ....................................................................... 4
2.2.2. Physical Biometrics ...................................................................................................... 5
3. FACE RECOGNITION ....................................................................................................... 7
3.1. Use of Face Recognition Systems ................................................................................... 7
3.2. Face Recognition Methods .............................................................................................. 8
3.2.1. Identification (recognition) ........................................................................................... 8
3.2.2. Verification (Authentication) ........................................................................................ 9
3.3. Face Recognition Processes ............................................................................................ 9
3.3.1. Face Detection (acquisition) ....................................................................................... 10
3.3.2. Preprocessing Face Image .......................................................................................... 10
3.3.3. Feature Extraction ....................................................................................................... 11
3.3.4. Feature Matching ........................................................................................................ 11
3.3.5. Training set ................................................................................................................. 12
3.3.6. Face database .............................................................................................................. 12
3.4. Dimensions used by Face Recognition ......................................................................... 12
IV
3.4.1. 2-D (Two-Dimensional) ............................................................................................. 12
3.5. Face Recognition Advantages ....................................................................................... 13
4. LITERATURE REVIEW .................................................................................................. 15
4.1. Principal Component Analysis ...................................................................................... 15
4.2. Eigen Face Approach .................................................................................................... 16
4.3. Local Binary Patterns Approach ................................................................................... 17
5. METHOD/APPROACH .................................................................................................... 19
5.1. Overall Description ....................................................................................................... 19
5.2. Product Perspective ....................................................................................................... 19
5.3. System Interfaces Requirement..................................................................................... 20
5.4. User Interface Requirement Analysis ........................................................................... 20
5.5. Hardware Interfaces ...................................................................................................... 22
5.6. Software Requirements ................................................................................................. 23
5.7. Software Interface ......................................................................................................... 23
6. SYSTEM DESIGN & DEVELOPMENT ........................................................................ 24
6.1. Design Constraints ........................................................................................................ 24
6.2. Quality Features ............................................................................................................ 24
6.3. Login Screen Image ...................................................................................................... 24
6.4. Main Menu .................................................................................................................... 26
6.5. Capturing Images .......................................................................................................... 27
6.6. Training Process ............................................................................................................ 27
6.7. Face Detection ............................................................................................................... 29
6.8. Face Recognition ........................................................................................................... 30
6.9. Screen Object and Action.............................................................................................. 32
6.10. Database Development ............................................................................................... 32
6.11. Test ............................................................................................................................. 32
6.11.1. Test Items ................................................................................................................. 32
6.11.2. Unit Testing .............................................................................................................. 32
6.11.3. Integration Testing ................................................................................................... 33
6.11.4. Acceptance Testing .................................................................................................. 33
6.11.5. System Testing ......................................................................................................... 33
6.11.6. Test Case 1 – User Login ......................................................................................... 33
V
6.11.7. Test Case 2 – User Registration ............................................................................... 34
6.11.8. Test Case 3 – User Registration ............................................................................... 34
6.11.9. Test Case 4 – Search ................................................................................................ 35
6.11.10. Test Case 5–Add New Detected Face .................................................................... 35
7. RESULTS AND CONCLUSION ...................................................................................... 37
REFERENCES ........................................................................................................................ 44
CURRICULUM VITAE ......................................................................................................... 47

VI
ABSTRACT
Biometrics is a term used to define an individual’s DNA, hand geometry, face, etc. or behavioral
characteristics, such as hand signature, voice tone, keystrokes and so on. For that reason, these
biological characteristics are unique in every individual. In many situations, face recognition
related technologies are becoming more popular among biometric-based technologies as it
measures an individual’s natural data. Genetic biometrics generally used to authenticate and
identify individuals by analyzing their physical characteristics, such as fingerprint, eye iris, can act
as an additional security measure at Automated Teller Machines. Instead of using a bankcard, a
camera installed at the Automated Teller Machines would capture an image of the customer's face,
and compare it against the account holder's photos in the bank database to verify the customer's
identity. The purpose of this thesis is to present a Windows based real time application system
using face recognition algorithms. This new system can be applied in various different fields such
as identity verification and other potential commercial applications. Both Eigen and Local Binary
Patterns face algorithms were used to reduce the impact of light exposure that will affect the
accuracy of the system.
Keywords: Biometrics, Face Detection, Face Recognition, Eigen Faces, LBP algorithms.

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LIST OF FIGURES
Page No
Figure 2.1. Identification Mode ................................................................................................ 3
Figure 2.2. Verification Mode .................................................................................................... 4
Figure 2.3. Examples of behavioral biometric (a) Keystroke, (b) Signature ............................. 5
Figure 2.4. Examples of physical biometric that are commonly used ....................................... 6
Figure 3.1. Face Identification Method ...................................................................................... 8
Figure 3.2. Face Verification Method ........................................................................................ 9
Figure 3.3. A Framework for Face Recognition System ......................................................... 10
Figure 3.4. Example of 2D facial recognition technology ....................................................... 13
Figure 4.1. LBP operator.......................................................................................................... 17
Figure 5.1. Product Perspective of Face Recognition System ................................................. 19
Figure 5.2. Steps of Face Recognition System ........................................................................ 20
Figure 5.3. System Structure Requirement .............................................................................. 21
Figure 5.4. Activity Diagram of Face Recognition System ..................................................... 22
Figure 6.1. User Login Interface Screen .................................................................................. 25
Figure 6.2. User Create new Account Interface Screen ........................................................... 26
Figure 6.3. User Main Interface Screen ................................................................................... 27
Figure 6.4. Training Process .................................................................................................... 28
Figure 6.5. Trained Images ...................................................................................................... 29
Figure 6.6. Face Detection ....................................................................................................... 30
Figure 6.7. Face Recognition ................................................................................................... 31
Figure 6.8. User Search Using by Name .................................................................................. 31
Figure 7.1. Accuracy ratio under inconvenient conditions ...................................................... 37
Figure 7.2. Accuracy rate under normal conditions ................................................................. 37
Figure 7.3. Recognized Test Images Taken From Webcam .................................................... 37
Figure 7.4. Unknown Face ....................................................................................................... 38

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