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Motivation and Use Cases for NFIQ 2.0 

on behalf of 

Oliver Bausinger 

Federal Office for Information Security 

Christoph Busch 

Hochschule Darmstadt – CASED 
 

 

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Fingerprint Applications 

• Official documents with fingerprints 

• European ePassports 

• European Residence Permits 

• Identity Cards (partially) 

• European Visa Information System (VIS) 

• Tenprints from all Schengen (short-time) Visa applicants 

• Data stored for 5 years 

• Target size up to 100 Mio. records 

• Biometric verification at Schengen border checks has started 

• Criminal AFIS 

• Future RTP programs might use fingerprints 
 

 

 

 

 

 

 

 

Challenges for Operators 

• Problems 

• Technical 

• Heterogenous environments 

• Different software vendors and versions 

• Interoperability issues 

• System design 

• At enrolment stage, typically the biometric verification or identification system 

vendor is unknown 

• Large scale identification scenarios (AFIS) have 

high quality requirements 

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Challenges in fingerprint 

biometrics deployment (2) 

• Timing considerations 

• Timing constraints are the biggest driver in the design of an enrolment and 

verification process 

• For many instances, quality correlates directly with time 

• No only technical, but also organizational, e.g. user guidance 

• Time is expensive 

• Officers are expensive 

• Room is expensive 

• Which quality is required by the system? 

• How much time (on average) do I need to reach the desired level? 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Stages of possible quality control

• Scanner level 

• Hardware built-in auto capture 

• Hard to tweak to a specific application scenario 

• Capture software level 

• Beyond the vendor SDK 

• Run things like NFIQ, vendor software kits, other QA algorithms 

• Implement target system specific thresholds 

• Process level 

• A background system rejects the fingerprints 

• Trigger recapture only when necessary 

• Avoid this as often as possible because of timing considerations, especially 

when round trips to central systems are involved 

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Problem statement 

• There‘s no universal understanding of a term 

like fingerprint of sufficient quality 

• Sufficient for which application? 

• Quality requirements differ a lot for different applications 

(e.g obviously between 1:1 and 1:n) 

• But there‘s quality in the standards. 

• An algorithm should produce a value in [0, 100]. 

• Some do so... most don‘t 

• But still scores are not calibrated to an accepted base line. 

• And there is no consensus of thresholds for specific applications 

• OK, let‘s try ... NFIQ2.0 

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Motivation for NFIQ2.0 Framework 

• Modular approach for NFIQ2.0 development is desired 

• to be flexible regarding the implementation 

• to have a common basis of functionality needed for NFIQ2.0 development 

which might then be extended by exchange of certain modules 

• because project team is distributed and located all over the world 

• because only certain project partners have access to certain fingerprint 

databases 

• because work can be shared and re-used by others 

• to simplify the development process 
 

 

 

 

 

 

 

 

 

 

 

NFIQ 2.0 Development 

Tools NFIQ 2.0 NFIQ 2.0 light 

- extractQualityFeatures() 

- calculateUtility() 

- startTraining() 

- ... 

- checkQuality() 

...

Framework Image Format Converter 

Input/Output 

Interface Input/Output Module 

Quality Feature 

Extraction Interface 

Utility Estimation 

Interface 

Machine Learning 

Interface 

Quality Feature 

Extraction Module

Utility Estimation 

Module

Machine Learning 

Module 

- Fingerprint images 

- Quality features - Utility computation - Prediction - Feature extraction - Comparison scores - Fusion & binning - Training 

- Utility values 

MLP 

Quality 

feature x 

... Utility x 

... ... Database 

... Filesystem 

Architecture of NFIQ2.0 Framework 

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Context - I 

• Based on ISO/IEC IS 29794-1:2009 

"Information technology - Biometrics sample quality Part 1: Framework" 

• Definitions 

• quality: "the degree to which a biometric sample fulfils specified requirements for a 

targeted application" 

• quality score: "a quantitative expression of quality" 

• utility: "the observed performance of a 

biometric sample or set of samples 

in one or more biometric systems " 

• Biometric data quality blocks 

• Quality score 

• 0: lowest quality 

• 100: highest quality 

• 255: failed attempt to 

assign a quality score 
 

 

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Context - II 

• Linked to ISO/IEC rev 29794-4:201x 

"Information technology - Biometrics sample quality 

Part 4: Finger image data" 

• Quality feature classes 

• Global features 

• Local features (blockwise) 

• Expected return of research investment 

• Revision of ISO/IEC IS 29794-4:201x 

• Upgrade to an IS (International Standard) 
 

 

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Problem statement (2 nd try) 

• There‘s no common language to establish an interoperable definition of 

fingerprint of sufficient quality for a specific application scenario 

• When developing an application scenario, define a common understanding of the 

required image quality 

• We need the language for doing this 

• And we need a baseline tool for doing this 
 

 

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Expectations for the future 

• NFIQ2.0 will be good enough to be used as baseline tool 

for defining fingerprint of sufficient quality 

• NFIQ2.0 will be the calibration base for vendor QA tools 

• Vendor QA tools will not go away, but – at least – for large scale applications will be 

comparable (statistically, not on a by-image-basis) to NFIQ2.0 

• Vendor QA tools should not have a need to augment NFIQ2.0 itself, but it should be 

sufficient for a vendor to define a specific threshold for a specific application 

• NFIQ2.0 will be used in all major fingerprint-based biometrics systems. 

• NFIQ2.0-lite will provide feedback on mobile devices 

• Of course, the term of fingerprint quality will not be stable, but the 

biometric community will have a way to adapt, refine, reformulate it 

according to the evolution of fingerprint technology 
 

 

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Questions 
 

 

 

 

 

 

Contact 

Federal Office for Information Security 

Inspection Infrastructures and Architectures 

Oliver Bausinger 

oliver.bausinger@bsi.bund.de 

Hochschule Darmstadt / Fraunhofer IGD 

Christoph Busch 

Christoph.Busch@igd.fraunhofer.de 

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