1. Introduction: What we know and don’t know about biometrics

2. Lecture Outline 1.Biometrics – Reality and Myths 2.Biometrics in Real Life 3.Basic Biometric Definitions

3. Hollywood Face Recognition Common misconceptions – 100% match to any image at any angle – Instantly recognize any person – Tied into a “super database” that knows who everyone is –Available to and in use by law enforcement Movie scene (Pubic domain)

4. Hollywood DNA Misconceptions – Access to a super database that has everyone’s DNA –Automatically and rapidly processes a sample Movie scene (Pubic domain)

5. Hollywood Fingerprints Screenshot from “Man in black” movie (Pubic domain)

6. Hollywood – information theft Parody on “Mission Impossible” scene (anonymous)

7. Face Recognition Today Today’s Reality –Affected by lighting, angle, quality of captured image –Requires a “high-end” computer for real-time face capture/processing –Many are stand-alone systems –Being evaluated, not deployed Ft. Lauderdale Airport, Florida

8. Face Recognition Today Today’s Reality –Varying confidence of match depending on application –Multiple unique and proprietary image formats make sharing hard –Intelligence images not available to local law enforcement or corrections –Data sharing across jurisdictions is a problem 100 known images in the database

9. Face Recognition Today Face Recognition Vendor Test 2002 and 2006 provides independent government evaluations of commercially available and mature prototype face recognition systems. Results available at http://www.itl.nist.gov/iad/894.03/f ace/face.html FRVT 2002 and 2006 evaluated performance on: High resolution still imagery (5 to 6 mega-pixels) 3D facial scans Multi-sample still facial imagery Pre-processing algorithms that compensate for pose and illumination

10. FpVTE Fingerprint Vendor Technology Evaluation The Fingerprint Vendor Technology Evaluation (FpVTE) 2003 is an independently administered technology evaluation of fingerprint matching, identification, and verification systems. Assessed the capability of 18 vendors fingerprint systems to meet requirements for large-scale and small-scale real applications. Consists of multiple tests performed with combinations of fingers and different types and qualities of operational fingerprints Conducted by the National Institute of Standards & Technology (NIST) between October and November 2003 on behalf of U.S. Department of Justice. Report made public in June 2004 at http://FpVTE.nist.gov

11. FpVTE Fingerprint Vendor Technology Evaluation Some of the Results Systems that performed most accurately were developed by NEC, SAGEM, and Cogent The most accurate systems are highly accurate. Given a false accept rate of 0.01% the results for NEC Large Scale Test system showed a false rejection rate of 0.4% The variables that had the largest effect on system accuracy were the number of fingers used and fingerprint quality. Different systems were distinguished by how they performed across the spectrum from good to bad (performance separation was really on “bad” quality).

12. Applications: Biometrics in Schools Eleven, Single-Eye LG Electronics IrisAccess 2200 Iris Recognition Cameras were Evaluated – 6 cameras within closed areas in 3 schools – 5 cameras were located outdoors with fabricated protective closures Unsuccessful attempts mostly due to camera capture errors (16%) and access attempts by unknown users (5.8%) Issues remaining include: –Tailgating (accepted users holding door open for others) – Ability to Capture Iris Outdoors (lighting) National News Reports Interior System exterior System

13. Applications: Biometrics in Correction Facilities Demonstration and Assessment of Facial Recognition Technology at Prince George’s County Correctional Facility Visionics (now Identix) system installed based on results of FRVT 2000 Required re-work of room lighting, addition of camera lights, and training of staff and system users. Interfaced with Staff and Volunteer Access Control System to verify identity of staff and volunteers upon entry and exit from the facility Augments manned access control station

14. When you walk into a building from a parking lot? When you shop at your favorite store? Go to your bank? Applications: Video surveillance

15. When you buy gas for your car? Pay at a toll booth? Video surveillance is a daily fact of life. Current motivation is mostly to avoid theft in commerce. Applications: Video surveillance

16. The ideal surveillance technology would be –non-contact –at a distance –non-cooperative also fast, cheap, and highly accurate. Face recognition has appeal because –it is non-contact –works at a “distance” –seems to not require cooperation –is potentially fast and cheap –claims high accuracy in research. Applications: Video surveillance

17. Biometric Technology Biometric Technology is concerned with representation, storage, matching, synthesis and visualization of biometric information. Tremendous advance has been achieved over the last few years in both fundamental theoretical development, matching and synthesis, as well as biometric hardware and software products.

18. Individual matchers Course discusses traditional and emerging technologies for fingerprint matching, face reconstruction, emotion animation, iris synthesis, voice recognition, signature and ear matching, and biometric fusion.

19. Identification People are identified by three basic means: ––Something they have (identity document or token) ––Something they know (password, PIN) ––Something they are (human body, character)

20. Traditional identification Traditional means of automatic identification: ––Possession-based(credit card, smart card) Use “something that you have” ––Knowledge-based (password, PIN) Use “something that you know” ––Biometrics-based (biometric identifier) Use something that relies on “what you are”

21. Problems with traditional biometrics Tokens may be lost, stolen or forgotten Passwords or PINs 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: ––$1 billion in credit card transactions ––$1 billion in fraudulent cellular phone use ––$3 billion in ATM withdrawals The traditional approaches are unable to differentiate between an authorized person and an impostor (person pretending to be somebody he/she is not)

22. What is biometrics Biometrics–science, which deals with the automated recognition of individuals based on biological and behavioral characteristics ––Scientific follow-on to Bertillon’s body measurements of the late 1800s Biometry–mathematical and statistical aspects of biology Biometric system–essentially an automatic pattern recognition system that recognizes a person by determining the authenticity of a specific biological and/or behavioral characteristic (biometric) possessed by that person

23. Verification Verification –recognizes a person by comparing the captured biometric characteristic with person’s biometric template (model) pre-stored in the system for THIS PERSON “Am I who I claim to be?” One to one match

24. Identification Identification –recognizes a person by searching the entire template database for a match “Who am I?” One to many matches

25. Uses of biometrics Physical access control (airport, office). Logical access control (bank account). Ensuring uniqueness of individuals (preventing double enrollment in some application, i.e. a social benefits program).

26. References and Links University of Calgary BT Lab web site Course text books Signal Processing Institute, Swiss Federal Institute of Technology web site http://scgwww.epfl.ch/ Biometric Systems Lab, University of Bologna http://bias.csr.unibo.it/research/biolab/