GEORGIAN TECHNIAL UNIVERSITY
Author:
doctoral student Maguli Bedineishvili
maguli1004@gmail.com
Research director:
doctor of technical sciences,
professor Levan Imnaishvili
limn54@gmail.com
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Biometrics:
Myths and
Reality
Definition of Biometrics
Perception of
"Biometrics"
Traditional
Static processing of
biological features
Modern
Person identification
technology, which uses human
physiological features
Biometric Characteristics
Fingerprint
Keystroke
Hand
Iris
Signature
Face
Voice
DNA
Estimation of Biometric Features
Biometric
Barriers to
universality
Worn ridges;
hard or finger
impairment
None
Hand
impairment
Visual
impairment
Speech
impairment
Distinctiveness
High
Low
Medium
High
Low
Permanence
High
Medium
Medium
High
Low
Collectability
Medium
High
High
Medium
Medium
Performance
High
Low
Medium
High
Low
Acceptability
Medium
High
Medium
Low
High
Potential for
circumvention
Low
High
Medium
Low
High
Actuality
million. USD
Revenue of Biometric Industry
Information of Acuity Market Intelligence
Actuality
2012-2017
Forecast of technologies
development
1.
2.
3.
4.
5.
Human body - energy generator;
Biometrics in service of information security;
Mind reading isn't already fiction;
Mobile phone everywhere and in everything;
Computer - personal assistant.
Segment of Market
Hand
Hand
geometry vein
Voice
Signature
Other
Iris
Fingerprint
58%
Face
History of Biometrics
Finger papillary lines:
 Depicted on the ancient construction by accident...
 Decorative, mystical elements...
 Person confirmation facility:
 China - 300 year B. C.
 Japan - 702 year A.D.
 Europe - XVII-XIX century
 USA - 1902 year A.D.
Ireland
Ancient China
History of Biometrics
1858 year
William Herschel: used handprint for
formatting agreement
Herschel's fingerprints, which was made within 57
years.
1880 year
Henry Faulds: for person identification
was offered using fingerprint
History of Biometrics
1882 year
Alphonse Bertillon processed the
technique for measuring the parameters
of prisoners' bodies (Bertillonage)
Francis Galton created the first system of
classification fingerprint
Using Scopes
Biometric control of physical access
Biometric control of logical access
Justice and law enforcement scope
Accounting of working time
Medical scope
Border control
Financial and transactional biometrics
Mobile devices
Biometric locks
Consumer biometrics
Learning institutions
Other using scopes of biometrics - convenience
Using Scopes
Fingerprint Types
Image Processing Algorithm
Fingerprints characteristics
The Functioning Principle of Biometric
System
Fingerprint
pattern
Fingerprint
Fingerprint
“map”
Biometric System Implementation
Ye s / N o
Matcher
(Threshold)
Preprocessor
Authentication
Te m p l a t e
Database
Feature
Extractor
Preprocessor
Enrollment
Identification Procedure
Verification Procedure
Errors of Recognition Stage
• FRR – False Rejection Rate
The system makes decision to reject a person, in
spite of that, he is already registered in the
database.
• FAR – False Acceptance Rate
The system makes decision to accept a person,
even if he isn't registered in the database.
Relation of First and Second Category
Errors
FAR
FAR
FRR
EER
FRR
Teachers Biometric Registration System
Implemented in Georgian
Technical University
Biometric Eectoral System
Implemented in Georgian
Technical University
Biometric accounting system of students attendance in
lectures
Developed in Georgian
Technical University
Biometric System of Students’ Admission in Examinations
Developed in Georgian
Technical University
GEORGIAN TECHNIAL UNIVERSITY
Biometrics:
Myths and
Reality
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