1. Assistant Prof. Dr.Abbas H.
Alasadi
Email : abbashh2002@gmail.com

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Sensors
Recording & converting biometric traits to
computer usable data ,sensors are needed.
e.g.. Fingerprint verification.
Lecture 1
Pages 22

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. 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. 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. 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. 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. 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. IDENTIFICATION
 Search
a sample against a database of
templates.
 Typical application: identifying fingerprints
?
Lecture 1
Pages 29

30. VERIFICATION
 Compare
a sample against a single stored
template
 Typical application: voice lock
?
Lecture 1
Pages 30

31. Practical Applications
FACE RECOGNITION
IRIS
RECOGNITION
Lecture 1
HANDGEOMETRY
FINGERPRINT
Pages 31

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. APPLICATIONS
Lecture 1
Pages 33

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. 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. Iris Scan
Image Acquisition →
Image Processing →
Template Creation →
Template Matching
 Uses to date:



Lecture 1
Physical access
control
Computer
authentication
Pages 36

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. 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. DNA IDENTIFICATION
 Widely
accepted for
crime scenes
 Twin problem
Lecture 1
Pages 39

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. 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. 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. Thank
you
Lecture 1
Pages 43