Assistant Prof. Dr.Abbas H.
Alasadi
Email : abbashh2002@gmail.com
Course Syllabus
1. Introduction to Biometrics
2. Fingerprint Recognition
3. Face Recognition
4. Iris Recognition
5. Hand G...
Course Syllabus
8. Voice Biometrics
9. A Palmprint Authentication System
10. On-Line Signature Verification
11. Hand Vascu...
Introduction to Biometrics


The term “biometrics” is derived from the Greek
words “bio” (life) and “metrics” (to measure...
Introduction to Biometrics


One of the oldest and most basic examples of a
characteristic that is used for recognition b...
Introduction to Biometrics


The concept of human recognition is also seen in
behavioral-predominant biometrics such as s...
Introduction to Biometrics


Some examples are:

•

In a cave estimated to be at least 31,000 years old,
the walls are de...
Introduction to Biometrics
• There is also evidence that fingerprints were used
as a person’s mark as early as 500 B.C.
“B...
Introduction to Biometrics
•

In early Egyptian history, traders were identified
by their physical descriptors to differen...
History of Biometrics


By the mid-1800s, with the rapid growth of cities
due to the industrial revolution and more
produ...
History of Biometrics


Influenced by the writings of Jeremy Betham and
other Utilitarian thinkers, the courts of this pe...
History of Biometrics
 This created a need for a formal system that recorded
offenses along with measured identity traits...
History of Biometrics


The other approach was the formal use of
fingerprints by police departments. This process
emerged...
History of Biometrics


The first such robust system for indexing
fingerprints was developed in India by Azizul
Haque for...
History of Biometrics


True biometric systems began to emerge in the
latter half of the twentieth century, coinciding wi...
Overview of Biometrics
“Biometrics” is a general term used alternatively to
describe a characteristic or a process.
A a ch...
Overview of Biometrics
Biometric systems have been researched and tested
for a few decades, but have only recently entered...
Overview of Biometrics
Example
deployments within the United States Government
include the FBI’s Integrated Automated Fing...
Overview of Biometrics
 Many companies are also implementing biometric
technologies to secure areas, maintain time record...
Overview of Biometrics
 A typical biometric system is comprised of five
integrated components:
1. A sensor is used to col...
Overview of Biometrics
4. A matching algorithm compares the new biometric
template to one or more templates kept in data s...
Sensors
Recording & converting biometric traits to
computer usable data ,sensors are needed.
e.g.. Fingerprint verificatio...
Biometric Modalities
 Commonly implemented or studied biometric modalities
include fingerprint, face, iris, voice, signat...
Characteristics of Biometrics
1. Universality





Universality: Every person should possess this
characteristic
In pra...
Characteristics of Biometrics
2. Uniqueness





Lecture 1

Uniqueness: No two individuals possess the same
characteris...
Characteristics of Biometrics


3. Permanence
 Permanence: The characteristic does not change in
time, that is, it is ti...
Characteristics of Biometrics


4. Collectability
 Collectability: The characteristic can be quantitatively
measured.
 ...
Biometrics Today
Voice
Infrared Facial and Hand Vein Thermograms
Fingerprints
Face
Iris
Ear
Gait
Keystroke Dynamics
DNA
Si...
IDENTIFICATION
 Search

a sample against a database of
templates.
 Typical application: identifying fingerprints

?

Lec...
VERIFICATION
 Compare

a sample against a single stored

template
 Typical application: voice lock

?

Lecture 1

Pages ...
Practical Applications

FACE RECOGNITION

IRIS
RECOGNITION
Lecture 1

HANDGEOMETRY

FINGERPRINT
Pages 31
APPLICATIONS


Physical access control of, for example, an airport.
Here the airport infrastructure, or travel infrastruc...
APPLICATIONS

Lecture 1

Pages 33
Finger-scan
A live acquisition of a
person’s fingerprint.
 Image Acquisition →
Image Processing →
Template Creation →
Tem...
FEATURES


Strengths:






don’t change over time
Unique

W
eaknesses: Scars

Attacks:





Lecture 1

Finger De...
Iris Scan
Image Acquisition →
Image Processing →
Template Creation →
Template Matching
 Uses to date:





Lecture 1

...
FEATURES


Strengths:




W
eaknesses:







300+ characteristics; 200 required for match
Fear
Discomfort
Algorit...
Hand Scan






Typical systems measure 90
different features:
 Overall hand and finger width
 Distance between joint...
DNA IDENTIFICATION
 Widely

accepted for
crime scenes
 Twin problem

Lecture 1

Pages 39
Template Size
Biometric
Voice
Face
Signature
Fingerprint
Hand Geometry
Iris
Retina
Lecture 1

Appr. Template Size
70k – 80...
2003 comparative share
Keyst r oke Scan
0. 3%

Faci al Scan
11. 4%

Hand Scan
10. 0%
M ddl ewar e
i
12. 4%

Fi nger Scan
5...
CONCLUSION
Trust in these electronic transactions
is essential to the healthy growth of
the global economy.
Finger scan, v...
Thank
you
Lecture 1

Pages 43
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  • Introduction to Biometric lectures... Prepared by Dr.Abbas

    1. 1. Assistant Prof. Dr.Abbas H. Alasadi Email : abbashh2002@gmail.com
    2. 2. Course Syllabus 1. Introduction to Biometrics 2. Fingerprint Recognition 3. Face Recognition 4. Iris Recognition 5. Hand Geometry Recognition 6. Gait Recognition 7. The Ear as a Biometric Lecture 1 Pages 2
    3. 3. Course Syllabus 8. Voice Biometrics 9. A Palmprint Authentication System 10. On-Line Signature Verification 11. Hand Vascular Pattern Technology 12. Introduction to Multibiometrics 13. Biometric System Security 14. Biometrics databases Lecture 1 Pages 3
    4. 4. Introduction to Biometrics  The term “biometrics” is derived from the Greek words “bio” (life) and “metrics” (to measure). Automated biometric systems have only become available over the last few decades, due to significant advances in the field of computer processing.  Many of these new automated techniques, however, are based on ideas that were originally conceived hundreds, even thousands of years ago. Lecture 1 Pages 4
    5. 5. Introduction to Biometrics  One of the oldest and most basic examples of a characteristic that is used for recognition by humans is the face.  Since the beginning of civilization, humans have used faces to identify known (familiar) and unknown (unfamiliar) individuals.  This simple task became increasingly more challenging as populations increased and as more convenient methods of travel introduced many new individuals into- once small communities. Lecture 1 Pages 5
    6. 6. Introduction to Biometrics  The concept of human recognition is also seen in behavioral-predominant biometrics such as speaker and gait recognition. Individuals use these characteristics, somewhat unconsciously, to recognize known individuals on a day-to-day basis.  Other characteristics have also been used throughout the history of civilization as a more formal means of recognition. Lecture 1 Pages 6
    7. 7. Introduction to Biometrics  Some examples are: • In a cave estimated to be at least 31,000 years old, the walls are decorated with paintings believed to be created by prehistoric men who lived there. Surrounding these paintings are numerous handprints that are felt to “have…acted as an unforgeable signature” of its originator. Lecture 1 Pages 7
    8. 8. Introduction to Biometrics • There is also evidence that fingerprints were used as a person’s mark as early as 500 B.C. “Babylonian business transactions are recorded in clay tablets that include fingerprints.” • Joao de Barros, a Spanish explorer and writer, wrote that early Chinese merchants used fingerprints to settle business transactions. Chinese parents also used fingerprints and footprints to differentiate children from one another. Lecture 1 Pages 8
    9. 9. Introduction to Biometrics • In early Egyptian history, traders were identified by their physical descriptors to differentiate between trusted traders of known reputation and previous successful transactions, and those new to the market. Lecture 1 Pages 9
    10. 10. History of Biometrics  By the mid-1800s, with the rapid growth of cities due to the industrial revolution and more productive farming, there was a formally recognized need to identify people. Merchants and authorities were faced with increasingly larger and more mobile populations and could no longer rely solely on their own experiences and local knowledge. Lecture 1 Pages 10
    11. 11. History of Biometrics  Influenced by the writings of Jeremy Betham and other Utilitarian thinkers, the courts of this period began to codify concepts of justice that endure with us to this day. Most notably, justice systems sought to treat first time offenders more leniently and repeat offenders more harshly. Lecture 1 Pages 11
    12. 12. History of Biometrics  This created a need for a formal system that recorded offenses along with measured identity traits of the offender. The first of two approaches was the Bertillon system of measuring various body dimensions, which originated in France. These measurements were written on cards that could be sorted by height, arm length or any other parameter. This field was called anthropometrics. Lecture 1 Pages 12
    13. 13. History of Biometrics  The other approach was the formal use of fingerprints by police departments. This process emerged in South America, Asia, and Europe.  By the late 1800s a method was developed to index fingerprints that provided the ability to retrieve records as Bertillon’s method did but that was based on a more individualized metric – fingerprint patterns and ridges. Lecture 1 Pages 13
    14. 14. History of Biometrics  The first such robust system for indexing fingerprints was developed in India by Azizul Haque for Edward Henry, Inspector General of Police, Bengal, India. This system, called the Henry System, and variations on it are still in use for classifying fingerprints. Lecture 1 Pages 14
    15. 15. History of Biometrics  True biometric systems began to emerge in the latter half of the twentieth century, coinciding with the emergence of computer systems.  The nascent field experienced an explosion of activity in the 1990s and began to surface in everyday applications in the early 2000s. Lecture 1 Pages 15
    16. 16. Overview of Biometrics “Biometrics” is a general term used alternatively to describe a characteristic or a process. A a characteristic: s 1. A measurable biological (anatomical and physiological) and behavioral characteristic that can be used for automated recognition. A a process: s 1.Automated methods of recognizing an individual based on measurable biological (anatomical and physiological) and behavioral characteristics. Lecture 1 Pages 16
    17. 17. Overview of Biometrics Biometric systems have been researched and tested for a few decades, but have only recently entered into the public consciousness because of high profile applications, usage in entertainment media (though often not realistically) and increased usage by the public in day-to-day activities. Lecture 1 Pages 17
    18. 18. Overview of Biometrics Example deployments within the United States Government include the FBI’s Integrated Automated Fingerprint Identification System (IAFIS), the US-VISIT program, the Transportation Workers Identification Credentials (TWIC) program, and the Registered Traveler (RT) program Lecture 1 Pages 18
    19. 19. Overview of Biometrics  Many companies are also implementing biometric technologies to secure areas, maintain time records, and enhance user convenience.  For example, for many years Disney World has employed biometric devices for season ticket holders to accelerate and simplify the process of entering its parks, while ensuring that the ticket is used only by the individual to whom it was issued. Lecture 1 Pages 19
    20. 20. Overview of Biometrics  A typical biometric system is comprised of five integrated components: 1. A sensor is used to collect the data and convert the information to a digital format. 2.Signal processing algorithms perform quality control activities and develop the biometric template. 3. A data storage component keeps information that new biometric templates will be compared to. Lecture 1 Pages 20
    21. 21. Overview of Biometrics 4. A matching algorithm compares the new biometric template to one or more templates kept in data storage. 5. Finally, a decision process uses the results from the matching component to make a system-level decision. Lecture 1 Pages 21
    22. 22. Sensors Recording & converting biometric traits to computer usable data ,sensors are needed. e.g.. Fingerprint verification. Lecture 1 Pages 22
    23. 23. Biometric Modalities  Commonly implemented or studied biometric modalities include fingerprint, face, iris, voice, signature and hand geometry... etc. Many other modalities are in various stages of development and assessment.  There is not one biometric modality that is best for all implementations.  Many factors must be taken into account when implementing a biometric device including location, security risks, task (identification or verification), expected number of users, user circumstances, existing data, etc. Lecture 1 Pages 23
    24. 24. Characteristics of Biometrics 1. Universality    Universality: Every person should possess this characteristic In practice, this may not be the case Otherwise, population of nonuniversality must be small < 1% Lecture 1 Pages 24
    25. 25. Characteristics of Biometrics 2. Uniqueness    Lecture 1 Uniqueness: No two individuals possess the same characteristic.  Genotypical – Genetically linked (e.g. identical twins will have same biometric)  Phenotypical – Non-genetically linked, different perhaps even on same individual Establishing uniqueness is difficult to prove analytically May be unique, but “uniqueness” must be distinguishable Pages 25
    26. 26. Characteristics of Biometrics  3. Permanence  Permanence: The characteristic does not change in time, that is, it is time invariant  At best this is an approximation  Degree of permanence has a major impact on the system design and long term operation of biometrics. (e.g. enrollment, adaptive matching design, etc.)  Long vs. short-term stability Lecture 1 Pages 26
    27. 27. Characteristics of Biometrics  4. Collectability  Collectability: The characteristic can be quantitatively measured.  In practice, the biometric collection must be:  Non-intrusive  Reliable and robust  Cost effective for a given application Lecture 1 Pages 27
    28. 28. Biometrics Today Voice Infrared Facial and Hand Vein Thermograms Fingerprints Face Iris Ear Gait Keystroke Dynamics DNA Signature Odor Retinal Scan Hand and Finger Geometry Lecture 1 Pages 28
    29. 29. IDENTIFICATION  Search a sample against a database of templates.  Typical application: identifying fingerprints ? Lecture 1 Pages 29
    30. 30. VERIFICATION  Compare a sample against a single stored template  Typical application: voice lock ? Lecture 1 Pages 30
    31. 31. Practical Applications FACE RECOGNITION IRIS RECOGNITION Lecture 1 HANDGEOMETRY FINGERPRINT Pages 31
    32. 32. APPLICATIONS  Physical access control of, for example, an airport. Here the airport infrastructure, or travel infrastructure in general, is the application.  Logical access control of, for example, a bank account; i.e., the application is the access to and the handling of money.  Ensuring uniqueness of individuals. Here the focus is typically on preventing double enrollment in some application, for example, a social benefits program. Security– authentication Forensic sciences– individualization   Lecture 1 Pages 32
    33. 33. APPLICATIONS Lecture 1 Pages 33
    34. 34. Finger-scan A live acquisition of a person’s fingerprint.  Image Acquisition → Image Processing → Template Creation → Template Matching  Acquisition Devices:     Lecture 1 Glass plate Electronic Ultrasound Pages 34
    35. 35. FEATURES  Strengths:     don’t change over time Unique W eaknesses: Scars Attacks:     Lecture 1 Finger Decapitation “Gummy fingers” Corruption of the database Surgery to alter Pages 35
    36. 36. Iris Scan Image Acquisition → Image Processing → Template Creation → Template Matching  Uses to date:    Lecture 1 Physical access control Computer authentication Pages 36
    37. 37. FEATURES  Strengths:   W eaknesses:      300+ characteristics; 200 required for match Fear Discomfort Algorithms may not work on all individuals No large databases Attacks:  Lecture 1 Surgery (M rity Re p o rt ) ino Pages 37
    38. 38. Hand Scan    Typical systems measure 90 different features:  Overall hand and finger width  Distance between joints  Bone structure Strengths:  Reasonably robust systems W eaknesses:  Accuracy is limited;  Bulky scanner Lecture 1 Pages 38
    39. 39. DNA IDENTIFICATION  Widely accepted for crime scenes  Twin problem Lecture 1 Pages 39
    40. 40. Template Size Biometric Voice Face Signature Fingerprint Hand Geometry Iris Retina Lecture 1 Appr. Template Size 70k – 80k 84 bytes – 2k 500 – 1000 bytes 256 bytes – 1.2k 9 bytes 256 – 512 bytes 96 bytes Pages 40
    41. 41. 2003 comparative share Keyst r oke Scan 0. 3% Faci al Scan 11. 4% Hand Scan 10. 0% M ddl ewar e i 12. 4% Fi nger Scan 52. 1% Lecture 1 Si gnat ur e Scan 2. 4% Voi ce Scan 4. 1% I r i s Scan 7. 3% Pages 41
    42. 42. CONCLUSION Trust in these electronic transactions is essential to the healthy growth of the global economy. Finger scan, voice authentication and signature verification are the three fastest-growing segments .Imagine a secure world without passwords. Lecture 1 Pages 42
    43. 43. Thank you Lecture 1 Pages 43

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