Introduction to Biometrics
Dr. Bhavani Thuraisingham
The University of Texas at Dallas
Lecture #13
Biometric Technologies: Some Physiological Biometrics
October 5, 2005
Outline
 Summary of Previous Lectures on Biometrics Technologies
 Some other biometrics
References
 Course Text Book, Chapter
 http://www.biometricsinfo.org/
 http://ctl.ncsc.dni.us/biomet%20web/BMRetinal.html
 http://www.howstuffworks.com/dna-evidence.htm
Summary of Previous Lectures on Biometrics
Technologies
 Fingerprint Scan
 Face Scan
 Iris Scan
 Voice Scan
Some Other Biometrics Technologies
 Hand Scam
 Retina Scan
 AFIS (Automated Finger print Identification System)
 Multimodal Biometrics
 DNA Biometrics
 Some Behavioral Biometrics
- Signature recognition
- Keystroke Dynamics
Hand Scan: Introduction
 This biometric approach uses the geometric form of the hand
for confirming an individual’s identity.
 Because human hands are not unique, specific features must
be combined to assure dynamic verification.
 Some hand-scan devices measure just two fingers, others
measure the entire hand.
 Features include characteristics such as finger curves,
thickness and length; the height and width of the back of the
hand; the distances between joints and all bone structure.
 Although the bone structure and joints of a hand are relatively
constant traits, other influences such as swelling or injury
can disguise the basic structure of the hand.
Hand Scan: Introduction (Concluded)
 To register in a hand-scan system a hand is placed on a
reader’s covered flat surface.
 This placement is positioned by five guides or pins that
correctly situate the hand for the cameras.
 A succession of cameras captures 3-D pictures of the sides
and back of the hand.
 The hand-scan device can process the 3-D images in 5
seconds or less and the hand verification usually takes less
than 1 second.
 Components include: Acquisition hardware, Matching
software, Storage
Hand Scan: How it works
 Hand geometry scanners such as those made by Recognition
Systems Inc. take over 90 measurements of the length, width,
thickness, and surface area of the hand and four fingers--all
in just 1 second.
 The technology uses a 32,000-pixel CCD digital camera to
record the hand's three-dimensional shape from silhouetted
images projected within the scanner.
 The scanner disregards surface details, such as fingerprints,
lines, scars, and dirt, as well as fingernails, which may grow
or be cut from day to day.
 When a person uses the scanner, it compares the shape of
the user's hand to a template recorded during an enrollment
session. If the template and the hand match, the scanner
produces an output--it may unlock a door, transmit data to a
computer, verify identification, or log the person's arrival or
departure time.
Hand Scan: How it works
 During enrollment, which takes approximately 30 seconds,
the user places the right hand in the reader three times. The
unit's internal processor and software convert the hand image
to a 9-byte mathematical template, which is the average of the
three readings.
 The user's template may reside in internal memory (capable
of holding over 27,000 users), or on other media such as a
hard disk or smart card chip.
 As opposed to such technologies as fingerprint, voice
recognition, and facial recognition, where a multitude of
vendors compete via their proprietary technology, hand
geometry technology is dominated by one company,
Recognition Systems, Inc. (RSI)
 Finger geometry is led by Biomet Partners.
Hand Scan: How it works (Continued)
 RSI's method for capturing the biometric sample is as
follows: To enroll, the users places his or her hand palm down
on the reader's surface.
 The user then aligns his or her hand with the five pegs
designed to indicate the proper location of the thumb,
forefinger, and middle finger.
 Three placements are required to enroll on the unit; the
enrollment template is a representation of the most relevant
data from the three placements.
 RSI's units use a 32,000-pixel CCD (charged coupled device)
digital camera, inferring the length, width, thickness, and
surface area of the hand and fingers from silhouetted images
projected within the scanner.
Hand Scan: How it works (Concluded)
 Over 90 measurements are taken, and the hand and fingers'
characteristics are represented as a 9 byte template. source:
Recognition Systems, Inc.
 Biomet Partners' technology is similar, but draws on the
shape and characteristics of the index and middle finger. The
data is saved as a 20 byte template.
 Hand geometry does not perform 1-to-many identification, as
similarities between hands are not uncommon.
 Where hand geometry does have an advantage is in its FTE
(failure to enroll) rates, which measure the likelihood that a
user is incapable of enrolling in the system. Fingerprint, by
comparison, is prone to FTE's due to poor quality
fingerprints; facial recognition requires consistent lighting to
properly enroll a user.
Hand Scan: Template Generation and Matching
 Distinctive features include height, width, thickness of the
hand
 Distinctive features of the hand and finger are extracted from
a series of 3-D images and recorded into a small templates
 False matching and false non-matching are possible due to
the fact that hands may swell and undergo changes
Hand Scan: Applications
 Hand geometry is currently among the most widely used
biometric technologies, most suitable for access control and
time and attendance applications.
 Hand scan is used reliably at thousands of places of
employment, universities, apartment buildings, and airports anyplace requiring reasonably accurate, non-intrusive
authentication.
 The nature of hand geometry technology is such that most
projects are fairly small-scale and involve only a handful of
readers, but there are some projects which incorporate
dozens of readers.
Hand Scan: Deployments
 INSPASS (Immigration and Naturalization Service Passenger
Accelerated Service System) project, one which allows
frequent travelers to circumvent long immigration lines at
international airports.
 Qualified passengers, after enrolling in the service, receive a
magstripe card encoded with their hand scan information.
Instead of being processed by passport control personnel,
INSPASS travelers swipe their card, place their hand, and
proceed with their I-94 to the customs gate.
 Nearly 50,000 people have enrolled in the service, and
approximately 20,000 verifications take place every month.
Travelers from 30 different countries are qualified to register
for INSPASS; pending budgetary constraints, the near-term
objective is to rollout the INSPASS project to over 20 airports
in the U.S.
Hand Scan: Market Size
 Hand geometry is projected to be one of the slowed growing
biometric technology through 2007.
 Because the range of applications in which hand geometry is
typically limited to access control and time and attendance, it
will draw a progressively smaller percentage of biometric
revenues.
 Overall, hand geometry revenues are projected to grow from
$27.7m in 2002 to $97.4m in 2007. Hand geometry revenues
are expected to comprise approximately 2.5% of the entire
biometric market.
Hand Scan: Strengths and Weakness
 Strengths
- Ease of use.
- Resistant to fraud .
- Template size - Using RSI, a template size of 9 bytes is
extremely small
User perceptions – non-intrusive
 Weaknesses
- Static design - largely unchanged for years.
- Cost
Injuries to hands
Accuracy, hand geometry, in its current incarnation,
cannot perform 1-to-many searches, but instead is limited
to 1-to-1 verification.
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Retina Scan: Overview
 Completely different from Iris Scan
 Camera captures the image of the retina
 Movements affects the images
 Need about 3 – 5 images for enrollment
 Distinctive features include network of blood vessels
 Glaucoma and other conditions may affect retina scan
 Template generation process will map the unique network of
blood vessels into a template
 Template is about 96 bytes
 Usually does one-many identification
 Good for highly secure environments
Retina Scan: Overview (Concluded)
 Strengths
- Resistance to false matching
- Stable characteristics
 Weakness
- Difficult to use
- User discomfort
- Limited applications
Retina Scan: Details
 Retinal scanning analyses the layer of blood vessels at the
back of the eye.
 Scanning involves using a low-intensity light source and an
optical coupler and can read the patterns at a great level of
accuracy.
 The user looks through a small opening in the device at a
small green light. The user must keep their head still and eye
focused on the light for several seconds during which time
the device will verify his identity. This process takes about 10
to 15 seconds total.
 There is no known way to replicate a retina, and a retina from
a dead person would deteriorate too fast to be useful, so no
extra precautions have been taken with retinal scans to be
sure the user is a living human being.
Retina Scan: Details (Continued)
 Retina scan is actually one of the oldest biometrics as 1930's
research suggested that the patterns of blood vessels on the
back of the human eye were unique to each individual.
 While technology has taken more time than the theory to be
usable, EyeDentify, founded in 1976, developed The
Eyedentification 7.5 personal identification unit, the first
retina scan device made for commercial use, in 1984.
 At this time, they are still the primary company for retinal
scan devices
 Retina scan is used almost exclusively in high-end security
applications
 It is used for controlling access to areas or rooms in military
installations, power plants, and the like that are considered
high risk security areas.
Retina Scan: Details (Concluded)
 Retina scan devices are provide accurate biometric
 The continuity of the retinal pattern throughout life and the
difficulty in fooling such a device also make it a great longterm, high-security option.
 The the cost of the proprietary hardware as well as the
inability to evolve easily with new technology make retinal
scan devices a bad fit for most situations.
 It also has the stigma of consumer's thinking it is potentially
harmful to the eye, and in general not easy to use.
AFIS
 Automated Fingerprint Identification System (AFIS)
technology is used in a variety of law enforcement and civil
applications.
 In law enforcement, fingerprints are collected from arrested
subjects and searched against local, state, regional, and/or
national fingerprint databases.
 The subject's ten fingerprints are acquired either through the
traditional ink-and-roll method or through an optical livescan
system, consisting of a sizeable fingerprint scanner, PC, and
imaging and transmission software
 The electronic fingerprints are submitted, along with
demographic data, to identify or verify the identity of the
subject.
AFIS (Concluded)
 Searches may take minutes, hours, or days, depending on the
quality of the information submitted, the size of the database
being searched, and the entity requesting the search.
 Law enforcement searches often return candidate lists used
to determine which of several possible matches is the best
match.
 Most widely used biometric technology
 AFIS is different from fingerprinting systems
- AFIS captures (in addition to templates) and uses image
analysis algorithm
Multimodal Biometrics
 A multimodal biometric system uses multiple applications to
capture different types of biometrics.
 This allows the integration of two or more types of biometric
recognition and verification systems in order to meet
stringent performance requirements.
 A multimodal system could be, for instance, a combination of
fingerprint verification, face recognition, voice verification
and smart-card or any other combination of biometrics.
 This enhanced structure takes advantage of the proficiency of
each individual biometric and can be used to overcome some
of the limitations of a single biometric.
DNA Biometrics
 Proving that a suspect's DNA matches a sample left at the scene of a
crime requires two things: Creating a DNA profile using basic
molecular biology protocols; Crunching numbers and applying the
principles of population genetics to prove a match mathematically
 Humans have 23 pairs of chromosomes containing the DNA
blueprint that encodes all the materials needed to make up your
body as well as the instructions for how to run it. One member of
each chromosomal pair comes from your mother, and the other is
contributed by your father.
 Every cell in your body contains a copy of this DNA; While the
majority of DNA doesn't differ from human to human, some 3 million
base pairs of DNA (about 0.10 percent of your entire genome) vary
from person to person.
 The key to DNA evidence lies in comparing the DNA left at the scene
of a crime with a suspect's DNA in these chromosomal regions that
do differ.