Biometrics
Austen Hayes and
Cody Powell
Overview
 What
is Biometrics?
 Types of Biometric Recognition
 Applications of Biometric Systems
 Types of Authentication
 Constraints on Biometrics
 Biometric Research at Clemson
What is Biometrics?
 Automated
method for recognizing
individuals based on measurable
biological and behavioral characteristics
Finger Print Recognition

Minutiae

Pattern Matching

Problems: sometimes
unusable
Vascular Pattern Matching
 LED
infrared light
 Fingers
and back
of hand
 Not
completely
viable
Iris Recognition

Uses infrared light

Converts Images to
vectors

Needs further
development
Facial Recognition
 Location
and
position of facial
features
 Dependent
on
background and
lighting conditions
Voice Verification

Factors: pitch,
intensity, quality and
duration

Text dependent

Text independent

Problems: include
background noise
Hand Geometry

Scan both sides of
hand

Primarily used for
verification

Not as accurate as
other methods
Dynamic Signature
 Factors:
velocity,
acceleration and
speed
 Mainly
used for
verification
 Problems:
forgers
could reproduce
Retina Recognition

One of the most secure
means of biometrics

Unique to each person

Unique to each eye

Problems: require effort
on the part of subjects
Other Types
 Keystroke
 Gait
 DNA
 Odor
Commercial Applications
 Computer
login
 Electronic
Payment
 ATMs
 Record
Protection
Government Applications

Passport control

Border control

Access Control
Forensic Applications

Missing Persons

Corpse identification

Criminal
investigations
Type of Authentication
 Authentication

1:1
 Verification

1:N
Constraints on Biometrics


Typical
“Constrained” Image
Constraints:






Lighting
Distance
Pose
Expression
Time Lapse
Occlusion
Constraints on Biometrics
 “Unconstrained”
Image
Biometrics Research at
Clemson
 Biometric
and
Pattern
Recognition Lab
 Goals:
1.
2.
Usable Biometrics
Unconstrained
Biometrics
Biometrics Research at
Clemson
 Aging
Research
Biometrics Research at
Clemson
 Demographics



Older vs. Younger
Males vs. Females
Geographic origin
of algorithms
Biometrics Research at
Clemson
 Periocular
Region
Recognition


Texture, color, eye
shape
Overcome facial
occlusion
Biometrics Research at
Clemson
 Ear



Recognition
Not affected by
aging or
expression
Covert collection
of images
Little research
performed
Conclusion
 Questions?
Sources






Biometrics.gov. Web. 05 Dec. 2011.
http://www.biometrics.gov/ReferenceRoom/Introduction.aspx
Jain, Anil K., Arun Ross, and Salil Prabhakar. "An Introduction to
Biometric Recognition." IEEE TRANSACTIONS ON CIRCUITS AND
SYSTEMS FOR VIDEO TECHNOLOGY 14.1 (2004): 4-20. IEEE Xplore.
Web. 5 Dec. 2011.
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1262027
Jain, Anil K., Patrick J. Flinn, and Arun A. Ross. Handbook of
Biometrics. New York: Springer. Web. 5 Dec. 2011.
http://libcat.clemson.edu/record=b2478857
Phillips, Jonathon P., Alvin Martin, C. L. Wilson, and Mark Przybocki.
"An Introduction Evaluating Biometric Systems." Computer 33.2
(2000): 56-63. IEEE Xplore. Web. 5 Dec. 2011.
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=820040
http://bprl.cs.clemson.edu/about.html
http://bprl.cs.clemson.edu/projects.html