1. Biometrics Viktor MINKIN minkin@elsys.ru

2. OutlineOutline Outline Introduction Biometric systems Biometric characteristics Fingerprints Unimodal systems Multi-modal systems Problems Links History and future

3. Introduction 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.

4. Introduction Terms and definitions Template Capture Comparison Database Enrollment Matching Token User

5. Introduction 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”

6. Introduction Application Passport control Access to secured areas Surveillance ATMs Computer logins E-commerce Medicine Psychology

7. Introduction 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

8. Introduction 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

9. Introduction 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”

10. Biometric 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

11. Biometric 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

12. Biometric 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

13. Biometric Systems Receiver operating characteristics (ROC) False Rejection Rate False Acceptance Rate Equal Error Rate

14. Biometric Systems FAR/FRR and comparison threshold

15. Biometric Characteristics Static (biological) parameters Fingerprints Face Iris Hand geometry / vein Retinal pattern Facial thermogram Lip information DNA

16. Biometric Characteristics Dynamic (behavior) biometric parameters Signature Voice Motion Pulse

17. Biometric Characteristics Market Shares

18. Biometric Characteristics Market development

19. Fingerprints Accurate Comparatively cheap hardware Questionable acceptance

20. Fingerprints 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

21. Fingerprints Capacity technology

22. Fingerprints Fiber optic technology

23. Fingerprints Fingerprint types Arches Loops Whorl Bridge Dot Ridge Ending Bifurcation Enclosure Minutia types

24. Fingerprints Core & Deltas

25. Fingerprints Fingerprint minutiae

26. Fingerprints Image transformation Source FFT Flow field Directional Directional Directional image 1 image 2 irregularity Code Smoothing Binarization Skeleton Skeleton Minutiae formation cleaning search

27. Fingerprints Comparative testing

28. Fingerprints Fingerprint information

29. Unimodal Systems Facial ID Illumination Head pose Occlusion

30. Unimodal Systems Hand Vein Questionable accuracy Hand geometry

31. Unimodal Systems Retinal Pattern Highest accuracy Even more intrusive than iris recognition

32. Unimodal Systems Facial Thermo image and VibraImage Non-intrusive Lie detection View-dependent Emotion control Depends heavily on Criminals detector human factors, Medical monitoring body temperature Psychology testing

33. Multi-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.

34. Multi-modal Systems: Fusion “Early integration” or “sensor fusion” Integration is performed on the feature level Classification is done on the combined feature vector Features Modality 1 Classifier Features Modality 2 Features Modality n-1 Features Modality n Identity

35. Multi-modal Systems BioFinger 3 - Elsys includes BiCard, VibraImage, 3D-Elsys is biological and behavioral identification system

36. Multi-modal Systems The World population in 2000 was about 6.000 M. people. The biometric document (ID card) market is more 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)

37. Problems Errors rate Misunderstanding of real advantages and problems Incomplete true about biometric systems

38. Links International Biometric Group - http://www.biometricgroup.comhttp://www.biometricgroup.com NIST - http://www.itl.nist.gov/div893/biometrics/http://www.itl.nist.gov/div893/biometrics/ Literature –http://www.itl.nist.gov/iaui/894.03/pubs.html#finghttp://www.itl.nist.gov/iaui/894.03/pubs.html#fing Patents - http://www.elsys.ru/patents.phphttp://www.elsys.ru/patents.php

39. Biometrics evolution 19 century- not automated identification 20 century- biometric identification 21 century- emotion recognition and detection

40. Viktor Minkin Biometrics minkin@elsys.ru Thank you! 2004