biometria eyes
TRANSCRIPT
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A collage of iris scans,
showing the many small details
that make these unique to each
individual. Even identical twins
have different iris scans
as well as fingertips, of course).
Photo: University of Cambridge)
Ravi Das
I I C S
An Introduction to Biometrics
Ever since the tragic events of 11
September
2001,
security is a topic
that has received much attention.
We keep hearing in the news about
security increasing at airports andseaports. There are many solutions
to security. However, there is one
solution that utilises a unique tech-
nological approach: Biometrics.
Biometrics leverages physiological
characteristics to identify and veri-
fy people. This article reviews in
some detail the biometric technol-
ogies that are availabie today, and
what is being envisioned for the
future.
Before examining the various biom etric tech-
nologies, it is important to expand upon the de-
finition of biometrics.
Biometrics Defined
While detective novels and cop shows have
long made us aware that our fingerprints are
unique, perhaps less known is the fact that our
bodies are unique in several other measurable
areas as well. Biometrics technology uses
those points of measurable uniqueness to de-
termine our identities, and acts as a front end to
This is how a facial recognition
a system that requires precise identification
before it can be accessed or used- That system
could be a sliding door with electronic locking
mechanisms, an operating device, or an app li-
cation where individual users have their own
rights and permissions.
Of course, this is partly what passwords
have done all along. Passwords determine
identity through user knowledge: If you know
the password, you can gain access to
system. The proDlem is that a password
nothing to do with your actual identity. P
words can be stolen, and users can give
passwo rds to others willingly or under
striction), resulting in a system that is far
open to far too many p eople. There is simp
foolproof way to make password-prote
systems completely safe from unautho
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ion system.
of the
Individuals have physiological features that
thought of as unique identifiers . More spe-
Biometrics are automated methods of recog-
The need for biometrics can be found in fed-
state and local governments, in the mili-
ready b enefiting from these
tech-
data protection, remote access to re-
ith other
tech-
Utilising biometrics for personal authentica-
tion is becoming convenient and considerably
more accurate than previous methods such as
the utilisation of passwords or PINs. This is
because biometrics links the event to a partic-
ular individual (as already commented, a pass-
word or token may be used by someone other
than the authorised user), is convenient (noth-
ing to carry or remem ber}, accurate (it provides,
for positive authentication), can provide an
audit trail and is becoming socially acceptable
and inexpensive-
By early 20 05, there was an impressive list of
34 countries that already had a national bio-
metric system in place or were developing it
Australia, the Bahamas, Belgium, Bosnia and
Herzegovina, Brazil, Brunei, Bulgaria, China,
Colombia, Denmark, Estonia, Finland, France,
Gernnany. Greece, Hong Kong, Ireland, Italy,
Lebanon, Malaysia, the Netherlands, New
Zealand,
Oman, Pakistan, Philippines, Portu-
gal, Qatar, Russia, Slovakia, Spain, Sweden,
Switzerland, the United Kingdom, and the
United States. The industrial implications are
self-evident. According to the International
Biometric Group, totai biometric industry reve-
nues grew from slightly less than $600 m illion in
2002 to more than $1.2 billion in 2004, and are
projected to attain $4-6 billion in 2008.
How Biometrics Work
Biometric systems consist of both hardware
and software; the hardware c aptures the salient
human characteristic(s), and the software inter-
prets the resulting data and determines accept-
ability.
At the most simple level, biometric systems
operate on a three-step process . First, a sensor
takes an observation. The type of sensor and
its observation will vary by biometric type.
Second,
the biometric system develops a way
to describe the observation mathematically and
produce a biometric signature. The method will
again vary by biom etric type , but also from ven-
dor to vendor. Third, the computer system in-
puts the biometric signature into a comparison
algorithm and compares it to one or more bio-
metric signatures previously stored in its data-
base. Other system components, or human
operators, then use these result(s) for other
actions such as allowing or denying access,
sounding an afarm, etc.
The crucial step in building an effective bio-
metric system is enrollment. During enrollment
each user, beginning with the administrator
who controls the system, provides samples of
from the scan and stores the data as a tem-
plate. You then interact with the biometric de-
vice again, and the system verifies that the da ta
corresponds to the template. It the software
fails to get a match, more tries may be needed,
just as dictation software learns tc recognise
the user's speech patterns over time. Once this
procedure is complete, the system is opera-
tional. The next time you try to access the sys-
tem, you are scanned by whatever device is
being used (you might be asked to supply a
user name as well), and the hardware passes
the data to the software, which checks the user
templates. If there Is a match, you are granted
access; otherwise, a message
reports
that
the
system can't identify the user.
Let's us now examine in detail a real world
example that utilises biometrics. The technolo-
gy is fingerprint recognition, and the scenario is
that of verification for physical access entry.
Imagine that you are trying to enter a high-
Sharbat Gula, first photographed
In
1984
when aged 12 in a refugee camp in
Pakistan by National Geographic
photographer Steve Curry, was traced
18 years later to a remote part of
Afghanistan vi/here she w as again p hoto-
graphed by Mr. Curry. Prof. John Daug man,
of the University of Cambridge Computer
Laboratory, established that these protraits
show the same person, by running his
iris recognition algorithms on m agnified
images of the eye regions in the two
photographs.
(Photo: University of Cambridge)
security area. Before you can enter this area,
you m ust first be in the database of people wh o
are authorised tc enter. To be included into this
database, you must first register your finger-
print through the enrollment process. During
enrollment, a number of pictures are taken of
your fingerprints. These pictures are called
samples, and the samples are then combined
to form one typical sample. A mathematical for-
mula called an extraction algorithm then
Ravi Das is the President of HT G Advance Systems.
Mr. Das
'
original article has been expanded by MT edi-
torial staff with additiona l material from a v ariety of
other open sources. The illustrations sourced lAEE
originate from the paper. An Introduction to Biometnc
Recognition ba Anil K.Jain Atun oss and Salil Prab
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Schematic diagram of the working
principle of a generic biometric system.
Sou rce: internet)
extracts the unique features from the sample,
whic h are stored into a file called an enrollment
template.
Now that you have completed the enrollment
process, you are ready for the next step - the
verification process. With verification, we are
attempting to answer the question Am I really
whom I claim to be? Imagine yourself once
again trying to acc ess the high security area. In
order to have authorisation to enter, you must
now verify yourself by placing your finger on
top of the sefisor of the fingerprint scanner. The
sensor will take a picture, or a sample, of your
fingerprint. The extraction algorithm will then
extract the unique features of your fingerprint
and store it into a file called a verification tem-
plate. The verification template is then com-
pared to the enrollment template to determine
how close the two templates match with each
other, via a mathematical formula called a
matching algorithm. Based o n this closeness, a
Block diagrams of enrol lment,
veri f icat ion an d identi f icat ion shown
using the four main modu les of
a biometric system, i.e. sensor, feature
extraction, matcher, and system database.
Source: IEEE]
SerEorDats
Registration or
Enroinent
Sensor Data
•>
-
Authentication
Venficationor
idertificabon
Threshold arxJ
Authenticate
1
YES NO
Find and Process
Biometnc
Information
*
Create Template
Find and Process
Siometnc
Information
Create Templets
Match and
Generate Score
number called a score is then co mpu ted. If this
score is greater than a value called a threshold
(this value is determined a nd set by the biom et-
ric system's administrator), you are then
authorised to enter the high security area. If the
score is less than the thres hold, you are denied
authorisation to enter, and the verification pro-
cess will repeat again. Although a lot does hap-
pen in the enrollment and verification process-
template
Quality
checker
Feature
Extractor
User interface
Enrollment
System DB
claimed identity
Feature
Extractor
Matcher
(1 match)
User interface
erification
one
template
True/False
System DB
Feature
Extractor
Matcher
N matches)
User interface
System DB
es,
they only take a m
of seconds to comple
It is important to ap
ciate the differ
between verification
identification With v
cation, the system
attempting to answer
question His this pe
really who they claim
be?
The previous ex
ple demonstrates veri
t ion.
With identifica
the system is rather tr
to found a person, th
supposed to be on
database. To asce
identity, the entire d
base of biometric
plates is searched
determine if there
match between your
plate and all of the o
templates in the datab
In other words, the
metric system is tryin
recognise you. A perfect example of identi
tion is AFIS (Automated Fingerprint Ide
cation Services) that is used by many law
forcement agencies to track known crimin
A specific application of the identific
process is the watchtist. In the watchlist ta
the biometric system determines If
individual's biometric signature matches
corresponding signature of someone o
watchlist. The individual does not make
Identity claim, and is some cases does not
sonally interact with the system in any
Examples of the watchlist task could be c
paring visitors to a public building against a
rorist database, or comparing John Doe
hospital to a missing persons list. The main
ference between standard identification pr
dures and the watchltst task is that while in
former case the person is supposed to be i
database and the system is trying to ide
him/her, in the latter the question is, Is
person in the database? If so, who are the
Biometric Technologies
The main biometric technologies avail
today include fingertip recognition, hand ge
etry recognition, facial recognition, voice
ognition, and iris/retinal recognition. The
geometry and the fingerprint recognition d
es have been around the longest. There
also other technologies which are b
explored today, and wiil be briefly discusse
Fingertip Recognition
Fingerprint recognition looks at the un
patterns found on fingertips. A greater va
of fingerprint recognition devices is avail
than for any other biometric. Some emulate
traditional police method of matching minu
i.e. the points o n the fingertips where print
es end or divide; others use straight pat
matching devices; and still others are a
more unique, including things like moire fr
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The fingerprint scanners shine a light through
A 100 match is not required - only one
Fingerprinting has a head start over other
High Accuracy. Fingerprint technology is
accurate; however, a fingerprint scanner
might deny access if you place too much or
too little pressure on it.
Undemanding.
Fingerprinting doesn't signifi-
cantly
dr in
computing resources-u nlike face
recognition (q,v,), which relies on full-motion
video,
Inexpensive. Fingertip scanners can even be
embedde d in keyboards and mice,
Easy Installation. Fingerprint scann ers are as
simple toset upa sa new keyboard and require
no tr ining to use.
As the prices of these devices and process-
fall,
using fingerprints for user verifi-
tech-
Fingerprint verification may be a good choice
s, where you can give users
ogies High, Medium and Low).
ource: lAEE}
The relationship between False
Accept R ate FAR) and the probability
of verification.
Source: FBI)
access application area seems to be based
almost exclusively on fingerprints, due to the
relatively low co st, small size, and ease of inte-
gration of fingerprint authentication devices.
On the other hand, fingertip recognition is
rather invasive as literally a hands-on te chno lo-
gy. Also, its simplest forms are rather easy to
spoof (for instance, simply breathing on a low-
cost PC mouse with built-in fingertrip recogni-
tion device may be enou gh to fool it), and som e
security implications should be carefully pon-
dered. For instance, fingerprint recognition
devices are being introduced on luxury cars,
but in April 2005 a band of car hijackers in
Kuala Lumpur simply chopped off a car's
owner finger to get around the vehicle's hi-tech
security system.
Facial Recognition
Recognising the shapes and positioning of
the features of a person's face is a complex
task, and facial recognition software has only
D N A
Far
[ dec
Facial thermogram
Fingerprint
Gai l
Hand geometry
Hand vein
Iris
Keystroke
Odor
Palmprint
Retina
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recently begun to accomplish it. First a camera
captures the image of a face, and then the s oft-
ware extracts pattern information it can com-
pare with user templates. Face recognition
uses one of two technique s. The first compa res
feature sizes and relationships, such as nose
length and the distance between your eyes.
The second method matches your most signif-
icant image data, like the size and shape of
your nose, ears, eyes and mouth with a record
of your face stored in a database.
Tbe m inutiae in a fingertips used by a
recognition system to create the template.
Photo: CNR)
With either method, no one has to share a
potentially grimy finger scanner. Better yet.
face recognition is completely unobtrusive and
requires no special action from the subject: the
system captures your face in moving video,
isolates features, and identifies them on the fly.
And,
the system is smart enough to recognis
your face even if you forgot to shave or your
eyes are bloodshot-
Facial recognition is highly accurate, and fur-
thermore the software provides an audit trail -
with time, date, and face print - of anyone try-
ing to break into the security system. On the
other ha nd, the system is rather expensive, it is
complex to set up, and is demanding in terms
of computing power. Facial recognition also
has some shortcomings when trying to identify
individuals in different environmental settings
(such as changes in lighting or/and changes in
the physical facial features of people, such as
new scars). Also, of all of the biom etric techn ol-
ogies, facial recognition has to deal the most
with privacy rights issues.
These aspects have slowed down its wide-
spread acceptance. Popular applications for
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Iris/Retinal Recognition
The two eye-based systems, iris and retina,
are generally considered to offer the best
security, because of tbe distinctiveness of the
patterns and the quality of tbe capture devices.
Further, the structure of the iris and the retina
rarely change over the lifetime of an individua l.
There has been some confusion between iris
and retinal recognition, in tbat tbe two are
apparently similar. However, the two technolo-
gies are very much different.
TTie pattern of the iris (the band of tissue that
surrounds tbe p upil of the eye) is com plex, w ith
a variety of characteristics unique in each per-
son.
Iris-based biometric involves analysing
features found in the colored ring of tissue that
surrounds tbe pupil. Iris scanning, undoubtedly
the less intrusive of the eye-related biometrics,
uses a fairly conventional camera element and
requires no close conta ct betwe en the user and
tbe reader. In addition, it has the potential for
higher than average template matching perfor-
mance. Iris biometrics work with glasses in
place and is one of the few devices that can
work well in identification mode. On the other
hand,
ease of use and system integration have
not traditionally been strong points with iris
scanning devices, but you can expect improve-
ments in tbese areas as new products emerge.
Some popular applications for ihs scanning
are verifying employees, and expediting the
immigration process for incoming passengers
at airports. Also, iris recognition has been used
to identify refugees seeking hu manitarian aid in
Afghanistan.
Retina recognition is probably the single
most secure of all biometric systems. It works
with the retina, the layer of blood vessels locat-
ed at the back of the eye near the optic nerve.
This technique involves using a low-intensity
light source through an optical coupler to scan
the unique p atterns of the retina. The only thing
that is actually determined is the pattern of the
blood vessels, but since this pattern is unique
in each person, identification can be precise.
Retinal scanning can be quite accurate, but
the retinal image is difficult to capture and dur-
ing enrollment the user must look into a recep-
tacle and focus on a given point while holding
very still so the camera can perform the cap ture
properly. This is not particularly convenient if
you wear glasses or are concerned about hav-
ing close contact with the reading device. For
these reasons, retinai scanning is not warmly
accepted by all users, even though the technol-
ogy itself can work well.
Retinal recognition is used for high security
physical access entry, such as nuclear and
government installations, where use r s acce p-
tance is not a matter for particular concern.
Hand Geometry Recognition
With the hand geometry system, the user
aligns a hand according to guide marks on a
hand reader hardware, and the reader capt
a three-dimensional Image of the fingers
knuckles and stores the data in a template
Hand geometry has been around for sev
years, and it was used for a security syste
the 1996 Olympic Games. It offers a good
ance of performance characteristics and is
atively easy to use. Accuracy can be very
if desired and flexible performance tuning
configuration can accommodate a wide ra
of application s. Further, ease of integration
otber systems and processes makes h
geometry an obvious first step for many
metric projects. Hand geometry might be
able where there are more users or whe re u
access the system infrequently and are
haps less disciplined in their approach to
system. The most popular applications so
are are time and attendance recording.
Finger Geometry Recognition
These devices are similar to hand geom
systems. The user places one or two fin
beneath a camera that captures the sha
and lengths of the areas of the finger and
knuckles. The system constructs a three
mensional image and matches the data aga
the stored templates to determine identity.
Palm Recognition
Similar to fingerprint recognition, palm
metrics (not to be confused w ith hand geo
Examples of biometric characteristics that are or could be used for biometric systems: a) DNA, b) ear, c) face,
d) facial therm ograph , e) hand therm ograp h, f) hand vein, g) fingerprint, h) gait, i) hand geo metry, j) iris, k) palmprint, I) retina, m) signatu
and n) voice.
Source: lAEE)
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) focuses on the various textures , such as
ges and other minutiae, found on the palm.
The voice recognttion method captures the
with
advanced voice systems can extend
long-
Voice authenticators use a telephone or
to work with background
Signature verification systems have one
rson's signature as proof of identity.
Actually, signature recognition systems, also
called dynamic signature verification systems,
go far beyond simply looking at the shape of a
signature: They measure both the distinguish-
ing features of the signature as such,
nd
the
distinguishing features of the process of
sign-
ing. These features include pen pressure,
speed,
and the points at which the pen is lifted
from the paper. These behavioural patterns are
captured through a specially designed pen or
tablet (or both) and compared with a template
of process patterns.
Bkxnvtrtc Acc*ss
Control Cofw ol*
QuatMh ESE-100O,
8 Port RS-232 Strtal O«vtc«
Eth«m«t
Top;
A fingerprint lock
system.
Photo: Smarthome)
Middle: IGI Infinite
Group and U ltra-Scan
Corp. have developed
an innovative fingertip
technology based on
ultrasonic scanning.
This is claimed to raise
scanning accuracy
to levels previously
unattainable within
the industry.
Photo: IGI)
The problem is that our
signatures vary significant-
ly over time and from one
instance to another, so
strong accuracy requires
multiple samples and an
extended verification pro-
cess.
Keyboard Dynamics
Keyboard dynamics is a
specific biometric tech nol-
ogy for computer access
security. It measures the
dwell time (the length of time you hold down
each key) as well as flight time (the time it takes
you to move between keys). Taken over the
course of several login sessions, these two
metrics produce a measurement of rhythm
unique to each user. Once the biometric data is
collected, it is encrypted and stored (locally In
the case of the desktop-only products, or in a
central database for the netvi/ork solutions).
When a user tries to log on, the software com -
pares the incoming biometric data against the
stored data. Biometrics template can also be
stored in a smart card which offers "persona
confidentiality" as the template need not be
stored in a central server (or service p roviders)
Other Technologies
There are other biometric technologies that
are being examined today, but there are no
commercial applications available yet. Re-
searchers are developing or examining the fea-
sibility of systems based on the analysis of
DNA (currently too slow to be of real use), vein
patterns, thermograms (facial, hand or hand
veins), gait recognition (the way people walk),
earlobe recognition, brain mapping, and even
bodily odours.
Limitations of Biometrics
The success of a biometric system is meas-
ured according to a number of criteria, and
each technology has both strengths and weak-
nesses. The most important criteria are con-
cerned with accuracy, and involve the con-
cepts of the False Reject Rate (also referred to
as FRR or Type t Errors), and the False Accept
Rate (a,k.a. FAR or Type 2 Errors). The False
Reject Rate can be defined as the proba bility o
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The dots represent the main measurement
points for a facial recognition system.
Photo: Automa)
the chances that a legitimate, registered user
will be denied access to the high security area
by the fingerprint scanner? The False Accept
Rate can be defined as the probability of an
impostor being granted authorisation by the
biometric system. For example, once again
referring to the verification scenario, what are
the chances that an impostor will be granted
access to the high security area by the finger-
print scanner?
It is important to appreciate that the FRR and
FAR are dependent not only on the technology
being used and the characteristics and perfor-
mance of the specific systems, but also and
indeed critically on the threshold level as estab-
lished by the administrator. Ideally, we vi/ould of
course like to be able to set our threshold so
that the probability of verification is 100 and
both the FRR and FAR are 0 . Unfortunately,
that is not possible, so we must compromise.
This compromise is a bit difficult, because the
probability of verification and the FAR are not
Denomination of the main points in the iris
that are useful for recognition purposes.
Photo: University of Cambridge)
The Handpunch 2000 hand geometry
recognition system
by Recognition Systems Inc.
Photo: Recognition Systems)
separated entities; rather, they are connected
with each other. If we raise the verification
threshold, the FAR decreases, but the probab il-
ity of correct verification also decreases. If we
lower the verification threshold, the probability
of correct verification increases, but so does
the False Accept Rate.
The False Accept Rate and the False Reject
Rate are two common criteria used in evaluat-
ing the performance of biometric systems, and
biometric product vendors often cite them in
their product descriptions. However, they don't
present a complete picture. The fact is,
people's physical traits change over time,
especially with alterations due to accidents or
aging.
And even in the short term, problems
can occur because of humidity in the air, dirt
and sweat on the user (especially w ith finger or
hand systems), and inconsistent ways of inter-
facing with the system, such as not taking
enough time for the system to make an accu-
rate identification. Further, users of biometric
systems, like the users of all systems, must be
trained to use them most efficiently.
These and other issues limit the accuracy of
biometric devices.
Still,
there's little doubt that
biometric systems are more accurate than
crypts
radial furrow i
pigment frill
pupilary area
ciliary are a
other kinds of security systems, beca
they're based on users' actual physical cha
teristics, not on what they knovi/ (as with p
words) or what they're carrying (such a
badges).
Biometrics success is also judged via a n
ber of other factors. Vulnerability to fraud,
known as barrier to attack, reflects how lik
is that a person can fraudulently get past
security (see below). Long-term stability d
with issues such as whether a system is u
for very infrequent users, as welt as whethe
not users' characteristics alter over time. O
effectiveness measures can include fac
that m ight interfere with the system , its size
its ease of use.
Vulnerability
The ease by which a biometric system
be defeated or spoofed determines its vu
ability. This encomp asses a numb er of d iffe
considerations, including:
- Liveness Examples include spoofing a
recognition device using a picture of
authorised person, or a tape recording o
authorised person's voice on speaker re
nition system;
- Deception Exampfes include an impo
attempting numerous hand geometry
numbers until he finds one for which his h
is a sufficient matc h, or a latex glove w ith
fingerprints of an authorised person mo
into it;
- Data Security The template informatio
some netvi/orked biometric sensors is tr
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mitted to a processor
or
analysis. Data secur-
ity in this contex t refers to the interception and
subsequen t m isuse of this data to circurTivent
the system;
The manner in which an unattended
device is installed may render it vulnerable
to
a
physical attack in an effort to defeat it. Some
devices used in access control applications
have built-in relays that unlock portals, so
opening the device and shorting these con-
tacts
vi ouid
be one way to defeat the system.
Some of the limitations inherent with uni-
Retina recognition
systems are arguably
the most secure
of all biometrics.
However, they are not
immune from user s
acceptance problems.
(Photo: biometricwatch)
Position and structure
of the retina.
(Photo: biometricwatch)
tems, are expected to be more reliable due to
the presence of multiple, independent pieces of
evidence. These systems are also able to meet
the stringent performance requirements im-
posed by various applications. Further, multi-
modal biometric systems provide anti-spoofing
measures by making it difficult for an intruder to
simultaneously spoof the multiple biometric
traits of a legitimate user. By asking the user to
present a random subset of biometric traits
5AFAEL^>
Muiti
iometric Login
dentification I nput data
r
The Retina
optic Nerve Head
(e,g.,
right index and right m iddle fingers, in that
order), the system ensures that a live user is
indeed present at the point of data acquisition.
Thus, a challenge-response type of authentica-
tion can be facilitated using multimodal biomet-
ric systems,
A multimodat biometric system can operate
in one of three different modes: serial mode,
parallel mo de, or hierarchical m ode. In the
seri-
al mode of operation, the output of one biomet-
ric trait is typically used to narrow down the
number of possible identities before the next
trait is used. This serves as an indexing sch eme
in an identification system. For example, a mul-
timodal biometric system using face and finger-
prints could first employ face information to
retrieve the top few matches, and then use fin-
gerprint information to converge onto a single
identity. This is in contrast to a parallel m ode of
operation where information from multiple traits
is used simultaneously to perform recognition.
This difference is crucial. In the cascade oper-
ational mode, the various biometric character-
istics do not have to be acquired simultaneou s-
ly. Further, a decision could be arrived at wi th-
out acquiring all the traits, which reduces the
overall recognition time. In the hierarchical
scheme , individual classifiers are combine d in a
tree-like structure.
Rafael was contracted by the Israeli MoD
to evaluate face recognition technologies
and determine whether these can be
used in the w ar against terrorism.
The outcome of the study suggested
multimodal biometrics, involving both
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