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OutlineIntroductionBiometric systemsBiometric characteristicsFingerprintsUnimodal systemsMulti-modal systemsProblemsLinksHistory and future
IntroductionIntroduction
Biometrics [harmonized]
Automated recognition of persons based on
their biological or/and behavioral characteristics.
Automated measurement of biological or/and
behavioral characteristics of person for medical,
security or psychological purposes.
IntroductionIntroduction
Terms and definitions
Template
Capture
Comparison
Database
Enrollment
Matching
Token
User
IntroductionIntroduction
Identification of a person
– Verification/Verify• Comparing one to one• “Am I who I claim I am”
– Identification• Comparing one to many• “Who am I”
IntroductionIntroduction
Application
• Passport control• Access to secured areas• Surveillance• ATMs• Computer logins• E-commerce• Medicine• Psychology
IntroductionIntroduction
Traditional means of automatic identification
(before biometrics)
– Knowledge-based• Use “something that you know”• Examples: password, PIN
– Token-based• Use “something that you have”• Examples: credit card, smart card, keys
IntroductionIntroduction
Problems with traditional approaches– Token may be lost, stolen or forgotten – PIN may be forgotten or guessed by the imposters
• (25% of people seem to write their PIN on their ATM card)
Estimates of annual identity fraud damages per year:– $1 billion in welfare disbursements– $1 billion in credit card transactions– $1 billion in fraudulent cellular phone use– $3 billion in ATM withdrawals
IntroductionIntroduction
The traditional approaches are unable to differentiate between an authorized person and an imposter
Use biometrics which relies on “who you are” or “what you do”
Biometric SystemsBiometric Systems
Requirements for an ideal biometric
– Universality• Each person should have the characteristic
– Uniqueness• No two persons should be the same in terms of the
characteristic
– Permanence• The characteristic should not change
Biometric SystemsBiometric Systems
Issues in a real biometric system
– Performance• Identification accuracy, speed, robustness, resource
requirements
– Acceptability• Extend to which people are willing to accept a particular
biometric identifier
– Faked protection• How easy is it to fool the system by fraudulent methods
Biometric SystemsBiometric Systems
Identification accuracy
• FAR = false acceptance rate• FRR = false rejection rate• EER = equal error rate• TER = total error rate = FAR + FRR• FER= false enrollment rate
Biometric SystemsBiometric Systems
Receiver operating characteristics (ROC)
False Rejection Rate
Fa
lse
Acc
ep
tan
ce R
ate
Equal Error Rate
Biometric SystemsBiometric Systems
FAR/FRR and comparison threshold
Biometric CharacteristicsBiometric Characteristics
Static (biological) parameters
Fingerprints
Face
Iris
Hand geometry / vein
Retinal pattern
Facial thermogram
Lip information
DNA
Biometric CharacteristicsBiometric Characteristics
Dynamic (behavior) biometric parameters
Signature
Voice
Motion
Pulse
Biometric CharacteristicsBiometric Characteristics
Market Shares
Biometric CharacteristicsBiometric Characteristics
Market development
FingerprintsFingerprints
Accurate
Comparatively cheap hardware
Questionable acceptance
FingerprintsFingerprints
Optical technology
Light reflects from the surface of the prism where the finger is not in contact with it, while it penetrates the surface of the prism where the finger touches the surface of the prism. The resulting image goes through a lens into a video camera.
Light source
Finger
Video Camera (CCD)
LensPrism
FingerprintsFingerprints
Capacity technology
FingerprintsFingerprints
Fiber optic technology
FingerprintsFingerprints
Fingerprint types
Arches Loops Whorl
Bridge Dot Ridge Ending Bifurcation Enclosure
Minutia types
FingerprintsFingerprints
Core & Deltas
FingerprintsFingerprints
Fingerprint minutiae
FingerprintsFingerprints
Image transformation
Source FFT Flow field Directional Directional Directional image 1 image 2 irregularity
Code
Smoothing Binarization Skeleton Skeleton Minutiae formation cleaning search
FingerprintsFingerprints
Comparative testing
FingerprintsFingerprints
Fingerprint information
Unimodal SystemsUnimodal Systems
Facial ID
Illumination
Head pose
Occlusion
Unimodal SystemsUnimodal Systems
Hand Vein Questionable accuracy
Hand geometry
Unimodal SystemsUnimodal Systems
Retinal Pattern
Highest accuracyEven more intrusive than iris recognition
Unimodal SystemsUnimodal Systems
Facial Thermo image and VibraImage
Non-intrusive Lie detectionView-dependent Emotion controlDepends heavily on Criminals detectorhuman factors, Medical monitoringbody temperature Psychology testing
Multi-modal SystemsMulti-modal Systems
Why multimodal [multiple] person identification?– Quest for non-intrusive identification methods
• No special purpose hardware needed• Works potentially at greater distances
– “Traditional” arguments for going multimodal:• Increasing performance• Increasing robustness
– Mono-modal recognition techniques are likely to reach in a close future a saturation in performance.
Multi-modal Systems: FusionMulti-modal Systems: Fusion
“Early integration” or “sensor fusion”Integration is performed on the feature level
Classification is done on the combined feature vector
FeaturesModality 1
Classifier
FeaturesModality 2
FeaturesModality n-1
FeaturesModality n
Identity
Multi-modal Systems Multi-modal Systems
BioFinger3 -Elsys includes BiCard, VibraImage,
3D-Elsys is biological and behavioral identification system
Multi-modal SystemsMulti-modal Systems
The World population in 2000 was about6.000 M. people.
The biometric document (ID card) market ismore than $6.000.000.000
There are 3 different ID card technologies:
1. Card with additional memory (chip, CD,..)
2. Card with 2d-bar code
3. BiCard (3D-Elsys)
ProblemsProblems
Errors rate
Misunderstanding of real advantages and problems
Incomplete true about biometric systems
LinksLinks
International Biometric Group
- http://www.biometricgroup.com
NIST
- http://www.itl.nist.gov/div893/biometrics/
Literature– http://www.itl.nist.gov/iaui/894.03/pubs.html#fing
Patents
- http://www.elsys.ru/patents.php
Biometrics evolutionBiometrics evolution
19 century- not automated identification
20 century- biometric identification
21 century- emotion recognition and detection
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