More about 

Biometric Databases

Brad Wing – NIST

Austin Hicklin - Noblis

26 January 2015
Basic Issues

 Can existing datasets be effectively used for new 

research?

 When collecting data for one purpose, is it costeffective (or even possible) to design it for multiple 

purposes?

 Can researchers ‘trust’ the data and metadata from 

existing sources?

 Will the sponsoring organizations allow the use of 

data from outside sources? IRB, copyrights, MOUs...
Basic Issues

 Is the size and ‘depth’ of databases sufficient? 

 Has ground truth been established?

 Have parameters of data collection been sufficiently 

categorized?

 How to the ‘holes’ in data needs get met?

 Can multiple existing data sources be effectively used 

instead of collecting new data for each study or grant? 
Is there data available?

 Need to ask:

 What data characteristics are needed to test / prove / 

disprove a hypothesis?

 Will the study be sufficiently affected if one or more of 

those characteristics is not present ?

 Database Catalogue as a resource

 To be covered as a talk in this conference

 Lists major characteristics of the known databases
Example:

Is altered data 

suitable for 

research ?

 CASIA-IrisV1 dataset 

From the website description: 

“In order to protect our IPR in 

the design of our iris camera 

(especially the NIR illumination 

scheme), the pupil regions of all 

iris images in CASIA-IrisV1 

were automatically detected and 

replaced with a circular region of 

constant intensity to mask out 

the specular reflections from the 

NIR illuminators. Such editing 

clearly makes iris boundary 

detection much easier but has 

minimal or no effects on other 

components of an iris 

recognition system, such as 

feature extraction and classifier 

design.” 
What about ‘outliers’?

Datasets may be ‘pure’ 

examples of ‘normal’ 

conditions or contain 

unusual cases. For iris, this 

may be optical diseases, or 

induced conditions 

(permanent or temporary) 

such as tattooed sclera or 

patterned / colored contact 

lenses. Images from BBC

http://www.bbc.com/news

/magazine-30750361
Controlled degraded data

Examples from

Q-FIRE (Quality in

Face and Iris Research

-Clarkson University

See http://www.clarkson.edu/biosal/pdf/quality.pdf
Training to data

 Databases may become so familiar to researchers that they 

tune their systems to ensure ‘success’

Note

problems

on left slap 

image -- from

NIST Special

Database 29
NIST software testing:

Use of sequestered data
Dataset size

 What is the minimum size 

needed to answer the 

question? 

 What is the amount of data 

that can be realistically / 

cost-effectively acquired?

 Will it be possible to 

extrapolate the analysis to 

larger dataset sizes? Should 

that be done?

 What are the assumed 

characteristics of the dataset 

as it grows? 

 Chart from: SUMMARY OF NIST 

STANDARDS FOR BIOMETRIC 

ACCURACY, TAMPER RESISTANCE, AND 

INTEROPERABILITY November 13, 2002 

http://biometrics.nist.gov/cs_links/pact

/NISTAPP_Nov02.pdf
Establishing ground truth

 Was data known at the time of capture (such as who 

spoke, what the words spoken were to be ...) ?

 Was data established by experts (such as when 

established ‘matches’ between a latent friction ridge 

print and an exemplar) ?

http://www.nist.gov/

oles/upload/7-

Phillips_P-JonathonChallenges-inForensic-FaceRecognition.pdf
Changes in features

 Possible? (Tattoo 

removal or alteration)

 Should these be 

included in datasets?

 Impossible? (Tooth with 

root canal becoming a 

virgin tooth)

 Should these be 

‘seeded’ in datasets?

http://www.newlookhouston.com/Tattoo_R

emoval_Photos.html
Data pedigree

 Has data been 

(unintentionally) altered? 

Such as through lossy 

compression of an image: 

 From “Comparison of the 

WSQ and JPEG 2000 Image 

Compression Algorithms On 

500 ppi Fingerprint Imagery” 

http://www.nist.gov/custo

mcf/get_pdf.cfm?pub_id=910

658
Aging of data

 Should samples be taken 

sequentially, in the same or 

different sessions?

 Should data (such as photos) 

be used that were taken in 

‘uncontrolled’ circumstances 

earlier?

 Is the object of the study the 

impact of aging or is aging a 

variable to be considered in 

analysis of the data?

 Can data from earlier in one’s 

life be compared against 

current data for the modality 

under study?

http://www.nist.gov/customcf/get_pdf.cfm?pub_i

d=915238

from American Society of 

Otolaryngologyhttp://www.entnet.org
Metadata about collection 

characteristics – voice example

 Voice analysis factors:

 Recording device type (including 

microphone)

 A-D conversion ?

 Data Compression?

 Frequency clipping?

 Environment

 Redactions / 

 Discontinuities

 Vocal content

 Type of speech (coerced, reading, 

spontaneous...)

 And more

Illustration from

www.Bnoack.com

(AV Info Non-Profit

Informational Website)
Protect Subject’s Privacy

Institutional Review Boards (IRBs) in US

 National Research Act of 1974

 Governed by Title 45 of 

Federal Regulations, Part 46

 Exemptions

 Research involving analysis 

of existing data and other 

materials if they are publicly 

available, or where the data 

can be collected such that 

individual subjects cannot 

be identified in any way

Universal Principles

 People should be informed if 

their personal information is 

being collected

 Personal information should 

only be used for the purpose 

for which it was collected

 Personal information should 

only be collected for a clearly 

identified purpose

As stated by the Office of the 

Privacy Commissioner of 

Canada www.priv.gc.ca
http://www.irb.cornell.edu

/forms/sample.htm

Participant Consent Sample 

from Cornell University 
Sample Database Use Form 

(License Agreement) from

From Notre Dame University

http://www3.nd.edu/~cvrl/Lice

nseAgreements/UNDLicenseAg

reementF.pdf
Cross-cultural issues

 Capture procedures for 

some biometrics may 

touch sensitive cultural 

issues (such as 

removing face veils)

 Paternity and familial 

relationship testing 

through DNA – how to 

handle socially sensitive 

results and how to handle 

perceived differences in 

definitions of a family 

http://www.dailymail.co.uk/news/article-2476772/DNA-test-confirmsBulgarian-woman-IS-natural-mother-blonde-haired-Maria.htm l
Cost Considerations

 Standards for how to 

collect data; amount 

needed, etc. Such as 

ISO/IEC 29794 that 

directly impact costs 

(number of participants, 

number of separate 

visits, etc. )

 Mike Thieme will 

discuss standards later 

in this conference

 Collection ‘pristine’ 

data for each 

experiment ....

 Paying participants 

and /or collection 

agents

 Spend time and money to 

verify existing datasets ...

 Signing use agreements 

 Review of data
Impacts upon Teaching

 Should data be collected as part of the teaching process?

(Hear talks Stephanie Schuckers and Jeremy Dawson)

 How to design experiments

 How to perform statistical analysis

 How to deal with regulatory requirements
Publishing study results

 Possible limitations based upon the terms of use of the datasets

 Can the images (or voice samples, etc.) be made publicly available in 

journals and other publications?

 How is reproducibility testing by other organizations to be done?

 Etc.

 Should data be aggregated for presentation to avoid privacy issues? Etc.

From:

IREX III Supplement I

Failure Analysis

http://www.nist.gov/custo

mcf/get_pdf.cfm?pub_id=9

10385
Company-sponsored data 

 Who does the research 

benefit?

 Why should people 

participate?

 Who ‘owns’ rights ---

DNA lines, etc.

 Can / should companysponsored data collection 

be used by researchers?

From: The Hand Vein Pattern Used as a 

Biometric Feature 

Master Literature Thesis by 

Annemarie Nadort, vreije 

Universiteit Amsterdam
Other factors

 When collecting data

 ergonomics

 accessibility

 universality

 understanding of 

instructions

 Formatting of data

 APIs for access, etc.

Those wishing to submit software for MINEX testing shall 

be required to provide NIST with an SDK (Software 

Development Kit) library which complies with the 

API (Application Programmer Interface) specified in 

this document. At a minimum, the SDK submitted 

must provide functionality to create MINEX 

compliant templates based on individual fingerprint 

images. Support for matching pairs of MINEX 

compliant templates is encouraged, but optional. 

http://www.nist.gov/itl/iad/ig/upload/

MINEX_API_041612.pdf

http://zing.ncsl.nist.gov/biousa/docs/

HFES%20instructions.ppsx