Biometric TechnologiesBiometric Technologies

Introduction to Biometrics Fingerprint Recognition

Eye – Retinal or Iris Recognition Dynamic Signature

Face Recognition Summary of Biometrics

Team 3:Team 3:Steven GolikovSteven Golikov

Barbara EdingtonBarbara EdingtonMelanie JohnsonMelanie Johnson

Bashir AmhedBashir AmhedBorming ChiangBorming Chiang

Introduction to BiometricsIntroduction to Biometrics

History of BiometricsHistory of BiometricsBiometrics is the study of biological “data”Biometrics is the study of biological “data”Biometrics has a very long traditionBiometrics has a very long tradition The Egyptians used the length of a person’s forearm to The Egyptians used the length of a person’s forearm to

determine their identification for wage paymentdetermine their identification for wage payment There are many different biometrics used for identification:There are many different biometrics used for identification:

FingerprintsFingerprintsEye – Retinal or IrisEye – Retinal or IrisFacial RecognitionFacial RecognitionVoiceVoiceSignatureSignatureDentalDentalDNADNAwww.biometricscatalog.orgwww.biometricscatalog.org

Iris and Retinal ScanningIris and Retinal Scanning

The Basics of Human EyeThe Basics of Human Eye

RationalesRationales

How do the Technologies Work?How do the Technologies Work?

ApplicationsApplications

Performance MetricsPerformance Metrics

Pros and ConsPros and Cons

Commercial ProductsCommercial Products

The Basics of Human EyeThe Basics of Human EyeIris –

•The Shutter of our biological camera

•The plainly visible colored ring underneath cornea.

•Iris surrounds the pupil

•A muscular structure which controls the amount of light entering into the eye, and it has very intricate details such as colors, striations, pits and furrows.

Retina –

•The film of the camera

•Located in the back of the eye where the Optic nerve connects.

•The blood vessels pattern in the retina are unique to each individual. Source: http://www.stlukeseye.com/Anatomy.asp

Rationales for UseRationales for UseIris contains intricate details such as striations, pits and furrows.

Two Iris’s are not alike. There is no detailed correlation between the patterns of identical twins or even between the left and right eye of the same individual.

Expressed by the Individual’s Phenotype, Not Genotype

The patterns of blood vessels in the retina is extremely unique to individuals.

There is no detailed correlation between the patterns of identical twins or even between the left and right eye of the same individual.

Source of images: http://www.cl.cam.ac.uk/users/jgd1000/

Iris Collage

Retinal Image - Twin 1 Retinal Image -Twin 2

How does Iris Recognition Works?How does Iris Recognition Works?

A picture of the eye is taken from within 1< meter A picture of the eye is taken from within 1< meter distance and Iris portion is extracteddistance and Iris portion is extractedAn Iris code of 512 Bytes is generated using An Iris code of 512 Bytes is generated using functions called 2-D wavelets. functions called 2-D wavelets. This code is unique This code is unique to one eye of one individual.to one eye of one individual.Iris code is then compared to other Iris codes that are Iris code is then compared to other Iris codes that are stored in the databasestored in the database

Source of images: http://www.iridiantech.com/

History of Iris RecognitionHistory of Iris Recognition

•1936 – Idea proposed by ophthalmologist Frank Burch1936 – Idea proposed by ophthalmologist Frank Burch1949 - The idea documented in an ophthalmology 1949 - The idea documented in an ophthalmology

textbook by James Doggartstextbook by James Doggarts

1980's - The idea had appeared in 1980's - The idea had appeared in James Bond filmsJames Bond films, , but it still remained science fiction and conjecture.but it still remained science fiction and conjecture.

1987 - two ophthalmologists, Aran Safir and Leonard 1987 - two ophthalmologists, Aran Safir and Leonard Flom, patented this ideaFlom, patented this idea

1989 - John Daugman (then teaching at Harvard 1989 - John Daugman (then teaching at Harvard University) try to create actual algorithms for iris University) try to create actual algorithms for iris recognitionrecognition

John Daugman algorithms patented in 1994, are the John Daugman algorithms patented in 1994, are the basis for all current iris recognition systems and basis for all current iris recognition systems and productsproducts

Commercial Applications -IrisCommercial Applications -IrisThe major applications of this technology so far have been:

•Aviation security and controlling access to restricted areas at airports

London Heathrow, Amsterdam Schiphol, Frankfurt, Athens, and several Canadian airports, Charlotte/Douglas International Airport in North Carolina

•Database access and computer login•Access to buildings and homes •Hospital settings, including mother-infant pairing in maternity wards•Border control "watch list" database searching at border crossings

On the Pakistan Afghanistan border, the United Nations High Commission for Refugees uses these algorithms for anonymous identification of returning Afghan refugees receiving cash grants at voluntary repatriation centres

•Other law enforcement agency programs such Jail SecurityPrisoner Identification – 1994 - Prisoner Identification – 1994 - Lancaster County Prison in Pennsylvania became the first correctional became the first correctional facility to employ the technology.facility to employ the technology.

Performance ComparisonPerformance Comparison

Method Coded PatternMisidentification

rateSecurity Applications

Iris/Retinal Recognition

Iris code / Blood vessel pattern

1/1,200,000 HighHigh-security

facilities

Fingerprinting Fingerprints 1/1,000 Medium Universal

Hand ShapeSize, length and

thickness of hands

1/700 LowLow-security

facilities

Facial Recognition

Outline, shape and distribution of eyes and nose

1/100 LowLow-security

facilities

SignatureShape of letters,

writing order, pen pressure

1/100 LowLow-security

facilities

VoiceprintingVoice

characteristics

1/30 LowTelephone

service

Source: AIM Japan, Automatic Identification Seminar, Sept.14, 2001

Pros and ConsPros and ConsIris ScanningIris Scanning

The uniqueness of Irises, even The uniqueness of Irises, even between the left and right eye of between the left and right eye of the same person, makes iris the same person, makes iris scanning very powerful for scanning very powerful for identification purposes. identification purposes.

The likelihood of a false positive is The likelihood of a false positive is extremely low and its relative extremely low and its relative speed and ease of use make it a speed and ease of use make it a great potential biometric. great potential biometric.

The only drawbacks are the The only drawbacks are the potential difficulty in getting potential difficulty in getting someone to hold their head in the someone to hold their head in the right spot for the scan if they are right spot for the scan if they are not doing the scan willingly. not doing the scan willingly.

Retina ScanningRetina ScanningRetina scan devices are probably Retina scan devices are probably the most accurate biometric the most accurate biometric available today. The continuity of available today. The continuity of the retinal pattern throughout life the retinal pattern throughout life and the difficulty in fooling such a and the difficulty in fooling such a device also make it a great long-device also make it a great long-term, high-security option.term, high-security option.

The high cost of the proprietary The high cost of the proprietary hardware as well as the inability to hardware as well as the inability to evolve easily with new technology evolve easily with new technology make retinal scan devices a bad fit make retinal scan devices a bad fit for most situations. for most situations.

It also has the stigma of It also has the stigma of consumer's thinking it is potentially consumer's thinking it is potentially harmful to the eye, andharmful to the eye, and in in general, not easy to use.general, not easy to use.

Commercial Products and VendorsCommercial Products and Vendors

Iris scanning (very accurate, expensive)

Argus Solutions (Australia) http://www.argus-solutions.com Aurora Computer Services Ltd (Northampton, U.K.) Eye Ticket Corp. (Virginia, U.S.A.) Iridian Technologies [(formerlyIriScan, Inc.) Marlton, NJ, U.S.A. and Geneva, Switzerland Saflink (Redmond, WA, U.S.A.)]

Retinal scanning (very accurate, very expensive) - Retinal is more intrusive than iris recognition.

Eyedentify, Inc. (Delaware, U.S.A.) Microvision, Inc. (WA, U.S.A.) (RSD = Retinal Scanning Display) Retinal Technologies, Inc. (MA, U.S.A.)

Face RecognitionFace Recognition

Background Background

AlgorithmsAlgorithms

FERET/FRVTFERET/FRVT

ResearchResearch

Commercial ProductsCommercial Products

Face Recognition: The BasicsFace Recognition: The Basics

In simplistic form, In simplistic form,

A A signature is createdsignature is created from a sensor’s from a sensor’s observationobservation

An An algorithm normalizesalgorithm normalizes the signature the signature

A A matcher comparesmatcher compares the normalized structure the normalized structure to the database.to the database.

The AlgorithmsThe Algorithms

EigenfacesEigenfaces Standard Principle Components Analysis (PCA)Standard Principle Components Analysis (PCA)

PCA & LDAPCA & LDA LDA: Linear Discriminant AnalysisLDA: Linear Discriminant Analysis Combination based on the University of Maryland algorithm Combination based on the University of Maryland algorithm

tested in FERET.tested in FERET.

BaysianBaysian An Intrapersonal/Extrapersonal Image Distance Classifier based An Intrapersonal/Extrapersonal Image Distance Classifier based

on the MIT algorithm tested in FERET.on the MIT algorithm tested in FERET.

Elastic Bunch GraphingElastic Bunch Graphing Based on the USC algorithm tested in FERETBased on the USC algorithm tested in FERET Uses localized landmark features represented by Gabor jetsUses localized landmark features represented by Gabor jets

Elastic Bunch GraphingElastic Bunch Graphing

FERET and FRVTFERET and FRVT

FERETFERET DARPA and Army Research LaboratoryDARPA and Army Research Laboratory 1994-19961994-1996 A unified means of testing algorithms for easier A unified means of testing algorithms for easier

comparisoncomparison

FRVTFRVT Designed by Govt and Law enforcement agenciesDesigned by Govt and Law enforcement agencies 2000 and 20022000 and 2002 Tested ability to compare images to those stored in a Tested ability to compare images to those stored in a

databasedatabase Females and younger people were harder to Females and younger people were harder to

recognizerecognize

Current ResearchCurrent Research

3-D morphable models3-D morphable models Not as affected by lighting and pose as is 2-DNot as affected by lighting and pose as is 2-D MERL (Mitsubishi) and Ohio State UMERL (Mitsubishi) and Ohio State U Identical twin Israeli studentsIdentical twin Israeli students

Created a 3-D scanner that uses light to scan the imageCreated a 3-D scanner that uses light to scan the imageAlgos measure the distances between points and compare to Algos measure the distances between points and compare to database imagesdatabase images

FactorsFactors False positivesFalse positives Privacy issuesPrivacy issues Environment – lighting, movement, etcEnvironment – lighting, movement, etc

Commercial ProductCommercial Product

FaceIT (from Visionics / Identix)FaceIT (from Visionics / Identix) $100 $100 Developed from an algorithm out of Rockefeller Developed from an algorithm out of Rockefeller

UniversityUniversity

Viisage Viisage From MIT algorithm based on eigenfacesFrom MIT algorithm based on eigenfaces

TrueFace (from Miros then acquired by Sol TrueFace (from Miros then acquired by Sol Universe) Universe) FaceOK – (from Titanium Technology)FaceOK – (from Titanium Technology) $89$89 PC user securityPC user security

Introduction to Fingerprint Introduction to Fingerprint RecognitionRecognition

Fingerprint is the most referred biometric mechanism Fingerprint is the most referred biometric mechanism used today.used today.

Fingerprint has the uniqueness feature – the studies Fingerprint has the uniqueness feature – the studies shows that chance of same fingerprint between two shows that chance of same fingerprint between two individuals (even in twins) is one in one billion.individuals (even in twins) is one in one billion.

Fingerprint has been widely adopted (low cost) for Fingerprint has been widely adopted (low cost) for authentication, identification and criminal authentication, identification and criminal investigation.investigation.

Uniqueness of FingerprintUniqueness of Fingerprint

Fingerprint is unique because of the two distinct featureFingerprint is unique because of the two distinct feature PersistencePersistence – the basic characteristic of fingerprint – the basic characteristic of fingerprint

do not change in time.do not change in time. IndividualityIndividuality – one over 1 billions !! – one over 1 billions !!

Fingerprints are comprised of various types of ridge Fingerprints are comprised of various types of ridge patterns: left loop, right loop, arch, whorl and tented patterns: left loop, right loop, arch, whorl and tented arch. arch.

The discontinuities that interrupt these smooth ridge The discontinuities that interrupt these smooth ridge patterns are called patterns are called MinutiaMinutia. Minutiae are essentially . Minutiae are essentially terminations and bifurcations of the ridge lines that terminations and bifurcations of the ridge lines that constitute a fingerprint pattern constitute a fingerprint pattern

Fingerprint Fingerprint Capturing and AnalysisCapturing and Analysis

Fingerprint MatchingFingerprint Matching Minutae-based Minutae-based Correlation based - Correlation based - requires precision location requires precision location

of registration pointof registration point

Fingerprint ClassificationFingerprint ClassificationThe technique to assign a fingerprint into one of The technique to assign a fingerprint into one of

the several pre-specified types already established with the several pre-specified types already established with indexing mechanism indexing mechanism Fingerprint EnhancementFingerprint Enhancement

It is essential to incorporate a fingerprint It is essential to incorporate a fingerprint enhancement algorithm with respect to the quality of the enhancement algorithm with respect to the quality of the fingerprint images in the minutiae extraction module in fingerprint images in the minutiae extraction module in order to ensure the accuracy of automatic fingerprint order to ensure the accuracy of automatic fingerprint identification/verificationidentification/verification

The Identification Workflow of The Identification Workflow of Fingerprint Device Fingerprint Device

DemonstrationDemonstrationIdentix BioTouch® 200 USB Identix BioTouch® 200 USB

Fingerprint ReaderFingerprint Reader Hardware - Hardware - BioTouch® 200 USB BioTouch® 200 USB Fingerprint ReaderFingerprint Reader

Software - BioLogon Software - BioLogon for Windowsfor Windows

Dynamic Signature Dynamic Signature VerificationVerification

What is It?What is It?

UsesUses

AdvantagesAdvantages

DisadvantagesDisadvantages

FutureFuture

What is It?What is It?

On-line vs Off-line signature VerificationOn-line vs Off-line signature Verification

Vision-Based, Non-VisionVision-Based, Non-Vision

Dynamic Signature – unique as DNADynamic Signature – unique as DNA

Measures speed, pressure of the penMeasures speed, pressure of the pen

Captures x, y, z location of the writingCaptures x, y, z location of the writing

UsesUses

Point of Sale applicationsPoint of Sale applications

Workflow automationWorkflow automation

SecuritySecurity

Authentication – replaces password, Authentication – replaces password, PIN, keycards, identification cardPIN, keycards, identification card

Financial – account opening, withdrawalFinancial – account opening, withdrawal

Wireless device securityWireless device security

AdvantagesAdvantages

Signatures already accepted as a means of Signatures already accepted as a means of identification so people willing to accept electronic identification so people willing to accept electronic signature.signature.

Changes in signing are consistent and have Changes in signing are consistent and have recognizable pattern.recognizable pattern.

Is not forgotten, lost, or stolen, so simple and natural Is not forgotten, lost, or stolen, so simple and natural way for enhanced computer security and document way for enhanced computer security and document authorization.authorization.

unique to an individual and almost impossible to unique to an individual and almost impossible to duplicate.duplicate.

DisadvantagesDisadvantages

Secured authenticationSecured authentication

Difficult to segment strokes as writing Difficult to segment strokes as writing styles are varied and have no set styles are varied and have no set standardstandard

Electronic tablets or digitizers are bulky Electronic tablets or digitizers are bulky and complex.and complex.

FutureFuture

Administrative Simplification (AS) of the Health Administrative Simplification (AS) of the Health Insurance Portability and Accountability Act (HIPAA)Insurance Portability and Accountability Act (HIPAA)

IT expendituresIT expenditures

Frost & Sullivan - $5.7M in 2003 up to $123.3M by Frost & Sullivan - $5.7M in 2003 up to $123.3M by 20092009

Mobile phones, Internet, tablet PC’sMobile phones, Internet, tablet PC’s

PC/Network Access, e-Commerce and telephony, PC/Network Access, e-Commerce and telephony, physical access and surveillance businessesphysical access and surveillance businesses

Thank YouThank You

Have any questions or comments?Have any questions or comments?

Team 3:Team 3:Steven GolikovSteven Golikov

Barbara EdingtonBarbara EdingtonMelanie JohnsonMelanie Johnson

Bashir AmhedBashir AmhedBorming ChiangBorming Chiang