Jain Presentation Update

8/8/2019 Jain Presentation Update

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Multimodal Biometric SystemsMultimodal Biometric Systems

Anil K. JainDept. of Computer Science and Engineering

Michigan State University

http://biometrics.cse.msu.edu


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Unacceptable error rates using a single biometric

Noisy biometric data

Flexibility to provide one of several possiblebiometrics

Reduce failure to enroll rate (increase populationcoverage)

Difficult to employ fake biometric

Why Multimodal Biometrics?Why Multimodal Biometrics?


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At NY airports, an average of ~ 300,000 passengers pass through daily. If all of these used biometric-authenticated smart cards for identification,

there would be 6,000 falsely rejected (and inconvenienced) passengersper day for fingerprints, 30,000 for face and 45,000 for voice. Similarnumbers can be computed for false accepts

State-of-the-art Error Rates State-of-the-art Error Rates

2-5%10-20%Text

Independent

NIST

[2000]

Voice

1%10%Varied lighting,outdoor/indoor

FRVT[2002]

Face

2%2%20 years(average age)

FVC[2004]

Fingerprint

FalseAccept Rate

FalseReject Rate

TestParameter

Test


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Poor Quality Iris ImagesPoor Quality Iris Images

Drooping eyelids Large pupil Off-centered iris

Failure to enroll (FTE) for iris is ~7% *

* BBC News, "Long lashes thwart ID scan trial", 7 May 2004, news.bbc.co.uk/2/hi/uk_news/politics/3693375.stm


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What is Multimodal Biometrics?What is Multimodal Biometrics?


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Intra-modal Fusion: Combination of

Fingerprint Matchers

Intra-modal Fusion: Combination of

Fingerprint Matchers

Jain, Prabhakar, Chen, " Combining Multiple Matchers for a High Security Fingerprint VerificationSystem", Pattern Recognition Letters, Vol 20, No. 11-13, pp. 1371-1379, 1999.

1. Minutiae-basedDynamicStringHough

2. Filter-basedFingercode


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Intramodal Fusion: Multiple Fingers,

Matchers and Templates

Intramodal Fusion: Multiple Fingers,

Matchers and Templates


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Cost vs. performance

Throughput

Verification vs. Identification mode

Choice and number of biometrics

Level of fusion

Fusion methodology

Assigning weights to biometrics

Multimodal databases

Design of Multimodal SystemsDesign of Multimodal Systems


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Which Biometric Modalities to Fuse?

Fingerprint, Hand geometry

Fingerprint, Face, Hand geometry

Voice, Lip Movement

Ear, Voice

Palmprint, Hand geometryIris, FaceFacial thermogram, Face

Fingerprint, Voice, Hand geometry

Fingerprint, Face, VoiceFingerprint, FaceVoice, Face, Lip Movement

Voice, Face


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Multibiometric Login SystemMultibiometric Login System

Face

Fingerprint

Hand geometry

Casacaded versus Parallel mode of operation


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Levels of FusionLevels of Fusion

Ross, Jain, "Information Fusion in Biometrics", Pattern Recognition Letters, September 2003.


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Three commercial fingerprint matchers and oneface matcher with EER values of 3.96%, 3.72%,2.16% and 3.76 % , respectively, were combined

972 individuals in the database

The best EER values in individual columns (rows)are indicated with bold typeface (star (*) )

1.62*1.501.824.651.73Tanh

* 0.631.16* 0.635.430.94QLQ

1.861.721.795.28*1.71Z-Score

* 0.631.160.865.430.99Min-Max

UWMWMaxMinSum

Fusion TechniqueNormalizationTechnique

MW Matcher Weighting; UW User Specific Weights

Fusion of Commercial Fingerprint

and Face Systems

Fusion of Commercial Fingerprint

and Face Systems


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Min/MaxNormalization of matching scores

Sum Rule

1000 Subjects

Fusing Commercial Face &

Fingerprint Systems

Fusing Commercial Face & Fingerprint Systems


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Performance VariabilityPerformance Variability

S c a

l a b i l i t y

G e n e r a

l i z a

b i l i t y

E f f e c

t s o

f V i r t u a

l

S u

b j e c

t s


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Cascaded Multibiometric SystemCascaded Multibiometric System

Capture biometric measurements as needed(Sequential pattern recognition)

Verification - reduces the average verification time Identification - successively prunes the database

(indexing)

To reduce the average verification time, themodalities must be cascaded in the decreasingorder of accuracy

In user-friendly systems, the user can be allowed tochoose the order of the modalities


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Fusion of Matching Scores

AdditionalBiometric?

No

Yes

ResultsFusion of Matching Scores

Cascaded Multimodal Biometric SystemCascaded Multimodal Biometric System

AdditionalBiometric?

Yes

Results

ResultsNo


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Cascaded System Performance

28% of the genuine users required only fingerprint, 13% required bothfingerprint and face, and 59% required all three modalities

Impostors had to submit all three modalities

Documents

Jain Presentation Update