introduction: what we know and don’t know about biometrics

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

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Introduction: What we know and don’t know about biometrics. Lecture Outline Biometrics – Reality and Myths Biometrics in Real Life Basic Biometric Definitions. Hollywood Face Recognition. Common misconceptions 100% match to any image at any angle Instantly recognize any person - PowerPoint PPT Presentation

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

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

Page 2: Introduction: What we know and don’t know about biometrics

Lecture Outline

1. Biometrics – Reality and Myths2. Biometrics in Real Life 3. Basic Biometric Definitions

Page 3: Introduction: What we know and don’t know about biometrics

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)

Page 4: Introduction: What we know and don’t know about biometrics

Hollywood DNA

Misconceptions– Access to a super

database that has everyone’s DNA

– Automatically and rapidly processes a sample

Movie scene (Pubic domain)

Page 5: Introduction: What we know and don’t know about biometrics

Hollywood Fingerprints

Screenshot from “Man in black” movie(Pubic domain)

Page 6: Introduction: What we know and don’t know about biometrics

Hollywood – information theft

Parody on “Mission Impossible” scene

(anonymous)

Page 7: Introduction: What we know and don’t know about biometrics

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

Page 8: Introduction: What we know and don’t know about biometrics

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

Page 9: Introduction: What we know and don’t know about biometrics

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/face/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

Page 10: Introduction: What we know and don’t know about biometrics

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

Page 11: Introduction: What we know and don’t know about biometrics

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).

Page 12: Introduction: What we know and don’t know about biometrics

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

Page 13: Introduction: What we know and don’t know about biometrics

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

Page 14: Introduction: What we know and don’t know about biometrics

When you walk into a building from a parking lot?

When you shop at your favorite store?

Go to your bank?

Applications: Video surveillance

Page 15: Introduction: What we know and don’t know about biometrics

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

Page 16: Introduction: What we know and don’t know about biometrics

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

Page 17: Introduction: What we know and don’t know about biometrics

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.

Page 18: Introduction: What we know and don’t know about biometrics

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.

Page 19: Introduction: What we know and don’t know about biometrics

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)

Page 20: Introduction: What we know and don’t know about biometrics

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”

Page 21: Introduction: What we know and don’t know about biometrics

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)

Page 22: Introduction: What we know and don’t know about biometrics

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

Page 23: Introduction: What we know and don’t know about biometrics

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

Page 24: Introduction: What we know and don’t know about biometrics

Identification

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

Page 25: Introduction: What we know and don’t know about biometrics

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).

Page 26: Introduction: What we know and don’t know about biometrics

References and Links

• University of Calgary BT Lab web site• Course text books• Signal Processing Institute, Swiss Federal Institute of Te

chnology web site http://scgwww.epfl.ch/• Biometric Systems Lab, University of Bologna

http://bias.csr.unibo.it/research/biolab/