biometria eyes

8/18/2019 Biometria EYES

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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)


6/9

) 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


7/9

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


8/9

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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biometria eyes

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