Dr. C. N. Ravi Kumar
Professor & Head
Dept.of Computer Science & Engg.
What is biometric technologies?
Biometric technologies are essentially a
Pattern Recognition systems which
refers to the "automated methods of
identifying or authenticating the identity
of a living person based on a
physiological or behavioral
Need for Biometrics
PINS (Personal Identification Numbers) and
Passwords may be forgotten.
Token based method of identification like
passports and driver’s licenses may be
Some typical biometrics
Primarily Physical Features
Fingerprint or fingerscan
Strong Behavioral Component
Voice recognition (verification)
Signature recognition (dynamics)
Key stroke scan
Some Biometrics with Reduced
Odour (human scent)
Gait recognition (manner of walking)
Foot Geometry or Foot impression.
Storage Requirements are Higher
“Size” of the template as stored can be quite large
in comparison with a password
Some typical template sizes:
Hand geometry: 9
Iris: 512 bytes
Retina: 96 bytes
Customer Acceptance and Convenience
Does reduce reliance on customer memory
Often considered more convenient than a smartcard
Enrollment style and use of biometrics are easy
Most of the biometrics are fairly stable except for accident
They are more reliable and accurate
Scan takes about 1 second
Size roughly 250
1000 bytes for fingerprints (overall)
Technically, most commercial
used Biometric is finger scanning
Finger print technology
captures a representation of the
finger; it involves storing the
image of the finger and
Fingerprint scanning (
Minutiae based approach
The technology isn’t
devices can be
purchased for lower
Euclidian Distance Measure:
A Boon for all Biometric
Speed and Accuracy Claims
Most manufacturers claim high accuracy
False acceptance rates < 1 in 100,000
False rejection rates < 1 in 100
<1 second to recognize
<5 seconds to enroll
Fairly Complex in usage thus calls for greater discipline
from user's side.
Not the most accurate but not bad; since hands tend to
be similar, it doesn’t do well in a “discovery”
Storage requirements about 9
Usually a specialized reader device to measure aspects
such as length, width, thickness, and surface area of the
hand and fingers
Implementation is expensive since it involves high
How does it work
The camera captures an image of the hand, with the
help of a mirror. The silhouette of the hand is
extracted, and some geometrical characteristics stored.
( See Jain et al.
Accelerated Service System
Facial recognition is the most natural means of biometric
Two recognition systems
PCA (Eigen Faces)
LDA (Linear Discriminant Analysis)
Combination of PCA and LDA.
Dynamic link matching
Derivative of the above two.
Neural Network Mapping Technology.
between 2 random variables X, Y with expected
and Standard deviations
i’ is the probabilities of occurrence of
discrete random variables ‘xi’
Examples Iris Images
Gather data by a camera within 3 feet of eye
512 byte Iris Code represents the visible characteristics of
It is claimed that the odds of the same Iris Code being
returned by two different people is less than 1 in 10^(52)
Iris Code includes “266 spots” to distinguish between
irises (claim is most other biometrics have between 10
Iris Code may vary by as much as 25% for a given eye …
but the odds of two different eyes being 75% similar is
said to be 1 in 10^(16), so this seems acceptable
Algorithms used in iris recognition are accurate.
Iris Scan is based on visible qualities of the iris
A primary visible characteristic is the trabecular
meshwork, a tissue which gives the appearance of
dividing the iris in a radial fashion.
Other visible characteristics include rings, furrows,
freckles and the corona.
Retinal Scan technology is based on the
blood vessel pattern in the retina of the eye
and it provides unique basis for
Template size small
Very accurate representation
Changes likely only from degenerative
Harder to use than most and requires
of blood vessels that emanate from
the optic nerve and disperse throughout the
retina depends on individuals and never
No two retinas are the same, even in identical
Thermograms requires an infrared camera to
detect the heat patterns of parts of the body that
are unique to every human being (such as the face)
Normally expensive because of the sensors
Illumination Invariant Face
Recognition Using Thermal Infrared Imagery
(Solikinski & als)
Surface is smaller (approximately 1/25 or
1/20 of that of space) which allows working
with images of reduced spatial resolution.
More uniform distribution of colour, so that
all information is conserved.
Changes in the shape of ear is slower when
compared to ear.
Template comparison & matching
ATM machine use
Workstations and network access use
Travel and tourism
Internet transactions : E
Public identity cards : Ration cards,Driving Licenses
Day care: verify identity of individuals picking up
Banking and many more
Role of Smartcard in biometric
The combination of a smart card and
biometric logon delivers a two
Now a days a biometrics cast its offering into the market
with BioPassword LogOn for Windows NT. The
client/server biometrics application recognizes a user's
typing pattern and uses it to authenticate them to the
network. The software uses a mathematical algorithm to
record pressure, speed, and rhythm as a user types their
user name and password. The typing pattern is compared
against a template created when the software is initially
It's easy to steal a biometric after the measurement is
taken. Once someone steals your biometric, it remains
stolen for life; there's no getting back to a secure situation.
It doesn't handle failure very well.
Not all biometrics are 100% match.
Challenges in Biometrics
Variation in Intensity
Variation in Intensity
Complicated Cases in Occluded Images
Biometric systems are not flawless.
One way to enhance the technology is to employ two or
Perceptions of Biometrics
Association for Biometrics
The international Biometric Industry Association
BSI (German information security agency)
The Bio API Consortium
The extranet for security professionals