Week1 New Bio Metrics

8/8/2019 Week1 New Bio Metrics

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Biometrics



Topics Biometric identifier classification

Biometric identifier characteristics comparison

Multimodal Biometrics

Biometric Standards

Challenges in Biometrics



Identifiable biometric

characteristics Biological traces

DNA, blood, saliva, etc.

Biological (physiological) characteristics

fingerprints, eye irises and retinas, hand palmsand geometry, and facial geometry

Behavioral characteristics

signature, gait , keystroke dynamics, lip motion, voice



Example of banking application



Biometric identifiers

Courtesy of G. Bromba



Biometric Market Share



Comparison of biometric

techniques



Palm



Hand vein



Facial Thermogram



Ear print



Retina

Human eye has its own totally unique pattern of blood vessels.

Because of its internal location, the retina is protected from variationscaused by exposure to the external environment (unlike fingerprints).



Which Biometric is the Best? Universality (everyone should have this trait)

Uniqueness (everyone has a different value)

Permanence (should be invariant with time) Collectability (can be measured quantitatively)

Performance (achievable recognition accuracy, resources required, operating environment)

Acceptability (are people willing to accept it?)

Circumvention (how easily can it be spoofed?)



Selecting a Biometric

Selecting the right biometric is a complicatedproblem that involves more factors than just accuracy. It depends on cost , error rates, computational speed, acquitability, privacy and easyof use.



Ideal Biometric

CharacteristicsThe ideal biometric characteristics have five qualities:

Robust: Unchanging on an individual over time.

Distinctive: Showing great variation over the population.

Available: The entire population should ideally have thismeasure in multiples.

Accessible: Easy to image using electronic sensors.

Acceptable: People do not object to having this measurement taken on them.



Quantitative measuresQuantitative measures of these five qualities have been developed.

"Robustness" is measured by the "false non-match rate" (Type I error), the probability that a submitted sample will not match

the enrollment image. "Distinctiveness" is measured by the "false match rate" (Type II

error), the probability that a submitted sample will match theenrollment image of another user.

" Availability" is measured by the "failure to enroll" rate, theprobability that a user will not be able to supply a readable

measure to the system upon enrollment. " Accessibility" can be quantified by the "throughput rate" of the

system, the number of individuals that can be processed in aunit time, such as a minute or an hour.

" Acceptability" is measured by polling the device users.



Biometric System Goals A biometric system can be designed to test one of only two possible

hypotheses:

The submitted samples are from an individual known to thesystem

The submitted samples are from an individual not known to thesystem

Applications to test the first hypothesis are called "positive

identification" systems while applications testing the latter are

called "negative identification" systems.



Types of Biometrics Overt Versus Covert: The first partition is "overt/covert ". If the user is aware that a

biometric identifier is being measured, the user is overt. If unaware, the use iscovert. Almost all conceivable access control and non-forensic applications are overt.Forensic applications can be covert.

Habituated Versus Non-Habituated: This applies to the intended users of theapplication. Users presenting a biometric trait on a daily basis can be consideredhabituated after a short period of time. Users who have not presented the trait recently can be considered "non-habituated".

Attended Versus Non- Attended: This partition refers to whether the use of thebiometric device during operation will be observed and guided by system

management.

Open Versus Closed: If a system is to be open, data collection, compression andformat standards are required. A closed system can operate perfectly well oncompletely proprietary formats.



Generic Biometric System

A generic biometric system.



Multimodal Biometrics Multimodal Biometric system is a system

that uses more than one independent or

weakly correlated biometric identifier takenfrom an individual (e.g., fingerprint and faceof the same person, or fingerprints from twodifferent fingers of a person)



Multi-modal Systems: Fusion Early integration or sensor fusion

Integration is performed on the feature level

Classification is done on the combinedfeature vector



Multi-modal Systems: FusionLate integration or decision fusion

Each modality is first pre-classified independently

The final classification is based on the fusion of the outputs of the different modalities



Multimodal biometrics

systems Multimodal biometrics systems improve performance

A combination in a verification system improvessystem accuracy

A combination in an identification system improvessystem speed as well as accuracy

A combination of uncorrelated modalities (e.g.fingerprint and face, two fingers of a person, etc.) is

expected to result in a better improvement inperformance than a combination of correlatedmodalities (e.g. different fingerprint matchers)



Other work: classification FBI Fingerprint card (includes information on

gender, ethnicity, height , weight , eye color

and hair color) Wayman (1997) proposed filtering large

biometric databases based on gender andage

Givens et al. (2003) and Newham (1995)showed that age, gender and ethnicity canaffect the performance of a biometric system



International Standards

Bodies



Application Programming

Interface ( API) Biometrics is the automated use of

physiological or behavioral characteristics to

determine or verify an identity Standards for interfaces and methods for

performance evaluation are needed



Biometric Authentication

Systems Layers of interaction with biometric authentication

systems

Scope Standardization of generic biometric technologies to

support interoperability and data interchange between

applications and systems Included: common file formats, application programming

interfaces ( APIs), biometric templates, template protectiontechniques, related application/implementation profiles, methodologies for conformity



Basic Standards Bio API ± The most popular API in the

biometrics area

CBEFF ±

Common Biometric Exchange FileFormat

ANSI X9.84-2003 ± Biometric InformationManagement and Security for the Financial

Services Industry ISO/IEC 19794 ± Biometric DataInterchange Formats



Challenges in Biometrics Large number of classes (~ 6 billion faces)

Large intra-class variability

Small inter-class variability Segmentation

Noisy and distorted images

Population coverage & scalability

System performance (error rate, speed, cost)

Attacks on the biometric system

Every biometric characteristic has some limitations



Threats to Biometrics

The Modern Burglar



Matsumoto¶s Technique

Only a few dollars¶ worth of materials



Making the Actual Clone

You can place the ³gummy finger´ over your realfinger. Observers aren¶t likely to detect it when youuse it on a fingerprint reader.

Don¶t try this at home! (Matsumoto)



Summary There is wide variety of biometric identifiers that

posses different characteristics

Each biometric system should take into account theend goal of application

Multi-biometrics improve performance of individualmatchers and is active topic of current biometricresearch

Biometric standards are being developed, whilebiometric reliability is still a concern



Reference and Links Signal Processing Institute, Swiss FederalInstitute of Technology

http://scgwww.epfl.ch/ Biometric Systems Lab, University of Bologna

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

www.sciencedierect.com Textbooks 1 and 2 CPSC 601.20

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