BTC - 1 Biometrics Technology Centre (BTC) Biometrics Solution for Authentication Prof. David Zhang...

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Biometrics Technology Centre (BTC)

Biometrics Solutionfor

Authentication

Prof. David Zhang

DirectorBiometrics Technology Centre (UGC/CRC)

Department of ComputingHong Kong Polytechnic University

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Introduction to Biometrics

Fingerprint Recognition

Iris Recognition

Speaker Recognition

Signature Recognition

Face Recognition

Hand Recognition

Applications

Future Directions

Outline

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Why Biometrics?

Introduction

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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.

Questions

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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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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 .

Hence, the problem of identifying a person

continues to pose a great challenge.

Challenge

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It can overcome some of the limitations of traditional

technologies because - physically present at the point-of-

identification, 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.

Biometrics

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What Biometrics?

Introduction

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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 by Technology Type

Taxonomy of Biometrics

Biometrics

Physical Behavioral

Head HandSignature Voice

Others(Gesture, gait, Keystroke)

Face

IrisOthers(Ear, Retina,Dental)

Fingerprint

Hand Geometry

Palmprint

Others (finger)

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How Biometrics?

Introduction

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Biometrics Based Identify Procedure

Measures Extraction Comparing Makingof biometrics of features the features the decision

SensorImage &

SignalProcessing

DecisionTheory

PatternRecognition

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Biometrics Evaluation

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DEMODEMODEMODEMO

Demo

Demo

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Current State Stability and uniqueness: Based on a century of

examination, it is estimated that the chance of twopeople, including twin, having the same print is lessthan one on a billion.

Fingerprint identification is the most widespreadapplication of biometrics technology. First commercialABS was used in 1971.

Feature Set

Minutiae - Endpoint & junction of print ridges, andposition, direction & relation between them

Singular Point

Fingerprint Development

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Demo

DemoFingerprint

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Iris Development

Current State Iris features can be more easily obtained than other

features from eyes, like retina.

It is shown that an iris has more details than afingerprint. Highly detailed and unique texture willremain stable over decades of life.

Feature Set

Textures with striations, contraction furrows, pits,collagenous fibers, filament, crypts (darkened areasresembling excavations), serpentine vasculature, rings,and freckles

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Demo

DemoIris

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Palmprint Development

Current State It has relatively stable physical characteristics, basically

unalterable without trauma to the individual. Manyuseful features extracted from both fingerprint & handshape can be simultaneously obtained.

However, no palmprint system is currently used inautomatic biometric identification. Therefore, it isnecessary to develop a new approach to automatedpersonal 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

Palmprint

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Speech Development

Current State The least invasive of the biometric recognition

technologies and the most natural to use is speechsystem.

Just say a phrase, about a second long - any language ordialect - chosen by the user. A typical case is AT&TSmart Card.

Feature Set

Twenty parameters –Pits, speed, energy, density, and waveform

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Demo

DemoVoice

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Signature Development

Current State It should distinguish between person’s habitual parts

and those that vary with almost every signing.

Two methods: on-line & off-line, where wired pens &sensitive tables are need for on-line signature.

Feature Set

Off-line – Line segmentsH 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

Signature

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Face Development

Current State Using the whole face for automatic identification is a

complex task because its appearance is constantlychanging.

One effective approach may employ rule-based logicand a neural network for the image classificationprocess. The first face system is introduced in 1992.

Feature Set

Facial geometry - Size of eye, distance from eye to mouth, middle ofmouth to chin, side of eye to cheek, size of mouth,radius vectors and feature points

Face template -

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Demo

Face DEMO

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Hand Development

Current State It is a simple ABS, which features are obtained by

three-dimensional shape. Analysis is based on mea-surement and comparison of geometries.

As a biometric application, one hand geometry iden-tification device is commercially available in 1994.

Feature Set

Finger length, width, area, thick and their relationshipbetween fingers

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Demo

DEMOhand1.swf

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Biometrics Applications Summary of Application

Dental Recognition Forensics

DNA Recognition Forensics, medicine, genetics

Fingerprint Recognition/Verification

Immigration & naturalization, welfaredistribution, military identification, forensics,access control

Face Recognition/Verification

Suspect description & identification, missingpersons, licenses, credit card, welfaredistribution

Hand Verification Access control, immigration andnaturalization, services distribution

Signature Recognition/Verification

Signature verification, identification fromhandwriting

Iris Verification Access control

Voice Recognition/Verification

Speaker verification, phone service, speakerverification, access control

Biometrics Applications

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Biometrics in Banking Application

Credit Card

Telephone Banking

Intelnet Banking

Cheque

Safe Deposit Box

IRIS

Fingerprint

Palm print

Voice

Signature

Face

Hand/Finger

BiometricsBanking Services

Bankbook

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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

dooropen_voice.swf

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EXAMPLE 2: Law Enforcement

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DEMOface_card.swf

EXAMPLE 3: Smart Card

BTC - 1 Biometrics Technology Centre (BTC) Biometrics Solution for Authentication Prof. David Zhang...

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