Biometrics Technology Centre (BTC)
Biometrics Solution
for
Authentication
Prof. David Zhang
Director
Biometrics Technology Centre (UGC/CRC)
Department of Computing
Hong Kong Polytechnic University
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Outline
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Introduction to Biometrics
Fingerprint Recognition
Iris Recognition
Speaker Recognition
Signature Recognition
Face Recognition
Hand Recognition
Applications
Future Directions
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Introduction
Why
Biometrics?
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Questions
 In the modern world, there is an ever
growing need to identify individuals.
 Should this person be given access to
a secure system?
 Does this person have authorization
to perform a given transaction?
 Is this person a citizen of our country?
 Every day, questions like these which
are related to establishing the identity
of individuals are asked millions times.
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Current System
 Person have to use more and more IDs
 Possession (Key, Credit card, …)
 Knowledge (password, PIN, …)
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Challenge

None of these problems would exist if we could
always be certain people -
Who they say they are & the
documents they use are not counterfeit.

Positive identification is crucial!

There are more and more highly fraudulent
technologies in today’s complex society

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Hence, the problem of identifying a person
continues to pose a great challenge.
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Biometrics

It can overcome some of the limitations of traditional
technologies because - physically present at the point-ofidentification, i.e., “something which you are or you do”

Biometrics can provide
better security ,
increased efficiency, and improved accuracy.

Biometrics-based identification is emerging as
the most reliable method.
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Introduction
What
Biometrics?
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Introduction
 Biometrics
A measurable
physical characteristics
or personal behavioral
trait used to recognize
the identity, or verify
the claimed identity,
of an enrollee
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Examples of Biometrics
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Characteristics of Biometrics
 Universality
 Uniqueness
 Collectability
 Permanence
 Acceptability
 Circumvention
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Taxonomy of Biometrics
Biometrics
Physical
Head
Hand
Behavioral
Signature
Voice
Others
(Gesture, gait,
Keystroke)
Face
Iris
Hand Geometry
Others
(Ear,
Retina,
Dental)
Finger
print
Palm
print
Others
(finger)
Taxonomy by Technology Type
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Introduction
How
Biometrics?
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Biometrics Based Identify Procedure
Sensor
Measures
of biometrics
Image &
Signal
Processing
Pattern
Recognition
Extraction
of features
Comparing
the features
Decision
Theory
Making
the decision
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Biometrics Evaluation
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Demo
 Demo
DEMO
DEMO
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Fingerprint Development
Current State

Stability and uniqueness: Based on a century of
examination, it is estimated that the chance of two
people, including twin, having the same print is less
than one on a billion.

Fingerprint identification is the most widespread
application of biometrics technology. First commercial
ABS was used in 1971.
Feature Set
Minutiae Endpoint & junction of print ridges, and
position, direction & relation between them
Singular Point
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Demo
 Demo
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Iris Development
Current State
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Iris features can be more easily obtained than other
features from eyes, like retina.
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It is shown that an iris has more details than a
fingerprint. Highly detailed and unique texture will
remain stable over decades of life.
Feature Set
Textures with striations, contraction furrows, pits,
collagenous fibers, filament, crypts (darkened areas
resembling excavations), serpentine vasculature, rings,
and freckles
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Demo
De
mo
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Palmprint Development
Current State
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It has relatively stable physical characteristics, basically
unalterable without trauma to the individual. Many
useful features extracted from both fingerprint & hand
shape can be simultaneously obtained.

However, no palmprint system is currently used in
automatic biometric identification. Therefore, it is
necessary to develop a new approach to automated
personal identification by palmprint.
Feature Set
Minutiae (like fingerprint) and shape (like hand)
Principal line, wrinkle, delta point and region feature
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Demo
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Speech Development
Current State
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The least invasive of the biometric recognition
technologies and the most natural to use is speech
system.
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Just say a phrase, about a second long - any language or
dialect - chosen by the user. A typical case is AT&T
Smart Card.
Feature Set
Twenty parameters –
Pits, speed, energy, density, and waveform
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Demo
Demo
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Signature Development
Current State
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It should distinguish between person’s habitual parts
and those that vary with almost every signing.
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Two methods: on-line & off-line, where wired pens &
sensitive tables are need for on-line signature.
Feature Set
Off-line – Line segments
H line, V line, P line, N line, C curve, D curve, A curve,
V curve, S curve, Z curve, curve and circle
On-line Pen tip position (x, y), distance above the surface (h),
pressure (p), tilt angle (tx, ty) and velocity (vx, vy)
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Demo
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Face Development
Current State
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Using the whole face for automatic identification is a
complex task because its appearance is constantly
changing.
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One effective approach may employ rule-based logic
and a neural network for the image classification
process. The first face system is introduced in 1992.
Feature Set
Facial geometry Size of eye, distance from eye to mouth, middle of
mouth to chin, side of eye to cheek, size of mouth,
radius vectors and feature points
Face template BTC - 33
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Demo

DEMO
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Hand Development
Current State
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It is a simple ABS, which features are obtained by
three-dimensional shape. Analysis is based on measurement and comparison of geometries.
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As a biometric application, one hand geometry identification device is commercially available in 1994.
Feature Set
Finger length, width, area, thick and their relationship
between fingers
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Demo

DEMO
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Biometrics Applications
Biometrics Applications
Summary of Application
Dental
Recognition
Forensics
DNA
Recognition
Forensics, medicine, genetics
Fingerprint
Recognition/
Verification
Face
Recognition/
Verification
Hand
Verification
Signature
Recognition/
Verification
Verification
Immigration
&
naturalization,
welfare
distribution, military identification, forensics,
access control
Suspect description & identification, missing
persons, licenses, credit card, welfare
distribution
Access
control,
immigration
and
naturalization, services distribution
Signature verification, identification from
handwriting
Access control
Recognition/
Verification
Speaker verification, phone service, speaker
verification, access control
Iris
Voice
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Biometrics in Banking Application
Banking Services
Biometrics
Bankbook
Face
Credit Card
Hand/Finger
IRIS
Telephone Banking
Fingerprint
Intelnet Banking
Palm print
Cheque
Voice
Safe Deposit Box
Signature
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Typical Applications
 Verification systems
 computer login
 cheque cashing
 airport check-in

Identification systems
 Driving licences
 Walfare
 Police mug-shots
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EXAMPLE 1:
Access Control
DEMO
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EXAMPLE 2:
Law Enforcement
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EXAMPLE 3:
Smart Card
DEMO
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