Download - History of Bio Metrics
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Abstract:
Biometrics is seen by many as a solution to
a lot of the user identification and security
problems in todayUs networks. Password
abuse and misuse, intentional and
inadvertent is a gaping hole in network
security. This results mainly from human
error, carelessness and in some cases
maliciousness. Biometrics removes human
error from the security equation.
Our project will examine all the
technological and feasibility aspects as well
as the practical applications. We will look at
many different biometric methods of
identifying the user.
A wide variety of systems require reliable
personal recognition schemes to either
confirm or determine the identity of an
individual requesting their services. The
purpose of establishing the identity is to
ensure that only a legitimate user, and not
anyone else, accesses the rendered services.
Examples of such applications include
secure access to buildings, airports,
computer systems, cellular phones and ATMmachines. Biometric recognition, or simply
biometrics, refers to the automatic
recognition of individuals based on their
physiological and/or behavioral
characteristics. Biometrics allows us to
confirm or establish an individuals identity
based on who she is, rather than by what she
possesses (e.g., an ID card) or what she
knows (e.g., a password). Current biometric
systems make use of identifiers such as
fingerprints, hand geometry, iris, face and
voice to establish an identity. Biometric
systems also introduce an aspect of user
convenience. For example, they alleviate the
need for a user to remember multiple
passwords associated with different
applications. A biometric system that uses a
single biometric trait for recognition has to
contend with problems related to non-
universality of the trait, spoof attacks,
limited degrees of freedom, large intra-class
variability, and noisy data. Some of these
problems can be addressed by integrating
the evidence presented by multiple
biometric traits of a user (e.g., face and iris).
Such systems, known as multimodal
biometric systems, demonstrate substantial
improvement in recognition performance. In
this talk, we will present various
applications of biometrics, challenges
associated in designing fingerprint biometric
systems, state-of-the-art performance,
individuality of biometric identifiers, and
fusion strategies available to implement a
multimodal biometric system.
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History of Biometrics:
The term "biometrics" is derived from the
Greek words bio (life) and metric (to
measure).
Biometrics is becoming an interesting topic
now in regards to computer and network
security, however the ideas of biometrics
have been around for many years. Possibly
the first known example of biometrics in
practice was a form of finger printing being
used in China in the 14th century, as
reported by explorer Joao de Barros. He
wrote that the Chinese merchants were
stamping children's palm prints and
footprints on paper with ink to distinguish
the young children from one another. This is
one of the earliest known cases of
biometrics in use and is still being used
today.
In the 1890s, an anthropologist named
Alphonse Bertillion sought to fix the
problem of identifying convicted criminals
and turned biometrics into a distinct field of
study. He developed 'Bertillonage', a method
of bodily measurement whichgot named
after him. The problem with identifying
repeated offenders was that the criminals
often gave different aliases each time they
were arrested. Bertillion realized that even if
names changed, even if a person cut his hair
or put on weight, certain elements of the
body remained fixed, such as the size of the
skull or the length of their fingers. His
system was used by police authorities
throughout the world, until it quickly faded
when it was discovered that some people
shared the same measurements and based on
the measurements alone, two people could
get treated as one.
After this, the police used finger printing,
which was developed by Richard Edward
Henry of Scotland Yard, instead. Essentially
reverting to the same methods used by the
Chinese for years. However the idea of
biometrics as a field of study with usefull
identification applications, was there and
interest in it has grown.
Today we have the technology to realise the
aims, and to refine the accuracy of biometric
identification, and therefore the possibility
of making it a viable field.
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Definition:
Biometrics is the science and technology of
measuring and analyzing biological data. In
information technology, biometrics refers to
technologies that measure and analyze
human body characteristics, such as DNA,
fingerprints, eye retinas and irises, voice
patterns, facial patterns and hand
measurements, forauthenticationpurposes.
Kinds of biometrics:
Biometrics can be sorted into two classes:
Physical: fingerprint, face...
Behavioral: handwriting, voice...
but well, in some cases, it's hard to sort.
Biometric identification:
Identification is the process by which a
person can be identified by his
characteristics. To do this, data about the
defining characteristic, for example the
points where the ridges of a fingerprint split
or end, is usually enrolled and stored in a
database. Then, when the person wishes to
be identified, the characteristic is scanned so
that the computer can compare it to the dataalready stored in the database. Using
biometric identification is a more secure
method of identifying a person because the
characteristic in question is a part of that
person. This means that it cannot be easily
shared, traded, or stolen by another.
There are mainly two categories of
biometrics identification: physiological
characteristics and behavioral
characteristics. Physiological biometrics has
to do with the physical traits of a person, and
behavioral biometrics has to do with the
things that can change with the environment.
For example, a fingerprint, a physiologicalcharacteristic, does not usually change
except for accident or illness, but a
signature, a behavioral characteristic, can
change as a person ages. Examples of
physiological biometrics include
fingerprinting, retinal scans and handprint
scans. Behavioral biometrics includes
verifying signatures andvoice recognition.
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Fingerprints recognition:
Finger skin is made of friction ridges, with
pores (sweat glands). Friction ridges are
created during ftal live and only the
general shape is genetically defined. Friction
ridges remains the same all life long, only
growing up to adult size. They reconstruct
the same if not too severe injury.
Fingerprint analysis wastraditionally a skilled activity
performed by highly trained
professionals. Biometric
fingerprinting is a similar process,
though it uses a computer to
examine a digitally captured image
specifically to establish a person's
identity.
Each individual has a different set offingerprints from every other
individual in the world. This is often
referred to as a biometricfingerprint.
Biometrics is the study of howhumans differ from each other based
on biological factors, such as how
each person's fingerprints form
differently.
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Face recognition:
Face recognition uses mainly the following
techniques:
Facial geometry: uses geometricalcharacteristics of the face. May use
several cameras to get better
accuracy (2D, 3D...)
Skin pattern recognition (VisualSkin Print)
Facial thermogram: uses an infraredcamera to map the face temperatures
Smile: recognition of the wrinklechanges when smiling
Face detection: It refers to the science of
locating the faces of people in a scene. It is a
critical element of focusing software in
cameras, as well as the primary step in facial
recognition in unconstrained scenes: the face
must be detected before it can be compared
to known faces and identified. It can also be
used by newer software to organize photos
on your computer.
On cameras, face detection helps establish
how the focus should work in a picture.
Depending on the camera, face detection
technology can identify at least 10 faces in a
scene. Once they are identified, they can be
prioritized, and the focus can automatically
adjust to feature the high priority faces. The
cameras face detection is often shown to
the user through a series of one or more
rectangles overlaid on the scene. With the
face detected, the technology can also adjust
the exposure to make sure the subject is
properly shown, including compensating for
dark scenes or scenes with an illuminated
background.
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Iris recognition:
An "iriscode" is extracted from the iris, once
it has been localized
Iris recognition uses iris images captured in
the near infrared bandwidth. The iris color is
not used, this is rather the iris structure
which is recognized.
Iris biometrics is a biometrics identification
method executed by taking high-resolution
images of a persons eye. The technology
utilizes a camera to make a template of the
eye, taking note of the corneal reflection.
The process relies on converting the image
of the person's iris into a mathematical
algorithm. Each time a person's eye is
scanned, it is compared with the
mathematical data from the first scan. Part
of the eye is always covered by the eyelid.
The mathematical equation takes the eyelid
into account when matching a person to his
scan by subtracting the areas covered by the
eyelid from the data. This technology can be
used to identify one person in a crowd, or
match one person to their own identifying
information.
Iris scanning is used to protect sensitive
information and allow access only to certain
individuals. It is also used as a means of
national security in some places. Iris
biometrics are considered especially
reliable. As with any identification method,
there is still a chance of human error,
although it is less so than other technologies
since computations for iris identification are
performed by a computer.
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When compared to fingerprinting, another
method of biometrics authentication, iris
biometrics has several advantages. The iris
is an internal organ, protected against
damage from the environment. The makeup
of the iris is determined during gestation.
Though certain medical conditions and
surgical procedures can affect the color and
shape of the iris, the texture, which is what
is measured by the technology, remains
stable. Biometrics devices using iris scans
have succeeded at identifying the same
person for periods of more than 30 years.
Iris biometrics is considered more reliable
than the more popular retinal scanning
method since theretinais subject to changes
with age.
On the other hand, iris biometrics is still
considered a relatively new technology. For
example, it does not have the length of time
associated with fingerprinting. It is difficult
to perform at a distance, and a person not
holding his head still or not looking into the
camera may be misidentified. Poor image
quality and software failure are two factors
that may adversely affect iris biometrics
technologies.
Hand, finger geometry:
A camera capture an image of the hand, with
the help of a mirror to get also the edge. The
silhouette of the hand is extracted, and some
geometrical characteristics stored.
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Voice, laughter:
Voice authentication, also known as
speaker verification, is defined as the
automated verification of a persons claimed
identity, based on unique characteristics of
their voice. Voice biometrics is an area of
biometrics which focuses on identifying
people by voice, or voice print as it is
sometimes known. Biometrics in general
involves measuring unique biological
characteristics for the purpose of comparing
unknown samples against known samples,
usually with the goal of confirming
someone's identity. This technology has
attracted a great deal of attention in many
regions of the world because it has potential
for the security industry as well as other
areas of human endeavor.
When someone who is enrolled speaks into
a voice biometrics system for the purpose of
identification, the system compares the
voice against the voice prints it has on file.If it detects a match, it will indicate that the
person has been recognized and identified.
A display may bring up details about the
person, and the system may also activate a
door lock or similar device to allow
someone to pass into a secure area.
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A simple microphone is enough to record
the voice, then most of the algorithm are
analysing the voice spectrum
Handwriting / Signature:
Handwriting recognition, or signaturerecognition also called Dynamic Signature
Verification (DSV) analyses the way a user
signs. The signing features such as speed,
velocity and pressure exerted by a hand
holding a pen are as important as the static
shape of the finished signature.
Required material starts from a simple
scanner (in this case, speed & pressure are
not available and the recognition accuracy
decreases) to the tablet, a video camera, a
pen containing sensors or using ultrasonic
sensing.
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Keystroke dynamics:
Keystroke dynamics, also called typing
rhytms or typing recognition, analyses the
way a person types. Users enroll by typing
the same word or words a number of times.
Verification is based on the concept that the
rhythm with which a person types is
distinctive.
Statistics of timings between two personsshow the difference
Mouse dynamics:
You have to draw something, always the
same (your name or whatever) using the
mouse. Some relevant characteristics are
extracted (position, velocity, angle...) and
used for further recognition.
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Gait:
Gait recognition by radar focuses on the gait
cycle formed by the movements of a
person's various body parts move over time.
"The magic goal we're shooting for is
accuracy in the high 90 percent range,"
Geisheimer says. "We're not there yet, but
our initial results are encouraging and
promising."
Researchers correctly identified 80 to 95
percent of individual subjects, with
variances in that range among the three
experiment days.
The next step is to build a more powerful
radar system and test it in the lab and then
the field. In experiments last year, subjects
started walking 50 feet away from the radar
and then walked within 15 feet of it. But
researchers are now building a radar system
that can detect people from 500 or more
feet.
In the study of gait recognition by computer
vision, researchers distinguish theirapproach from others with a technique
called an activity-specific static biometric. A
static property -- for example, a person's leg
length -- is not a property of motion itself. It
can be measured from a single image.
"The advantage of measuring a static
property is that it is amenable to being done
from multiple viewpoints," Bobick says.
". Static measurements are view invariant,
and that is a tremendous advantage because
you can't control where someone goes."
Researchers are also developing statistical
analysis tools for using a small, easily
gathered database to predict how well a
particular biometric, including gait
recognition, will work on a largerpopulation.
These techniques will also help researchers
determine what gait recognition properties
to measure based on how well the
technology can measure them.
"You can work on your ability to improvemeasurements," Bobick says. "But if you're
not measuring something that is diagnostic,
there is no amount of technology that will
solve that problem with the biometric."
Still in its infancy, computer vision-based
gait recognition technology holds promise,
particularly for verification or screening, if it
is used in conjunction with other biometric
technologies and information, Bobick
predicts.
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Meanwhile, researchers are applying the
findings from studies funded by the federal
Defense Advanced Research Projects
Agency to ongoing research in
understanding human movement through
video. Associate Professor Irfan Essa
envisions applications in medical diagnosis.
Algorithms for gait recognition are at
development stage.
Headprint:
After separation of hair area from the
background in overhead imagery, extraction
of features that characterize the color and
texture of hair is done for identification
purpose. Although the visual appearance of
hair cannot be used as a long-term biometric
due to the nonrigid nature of hair, a realistic
scenario where the time interval between
gallery and probe imagery is short enoughcan achieve reliable performance.
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Nose:
Unlike other facial features used for
biometrics, such as eyes or ears, noses are
difficult to conceal and also arent changed
much by facial expression.
Dr Adrian Evans and Adrian Moorhouse,
from the Universitys Department of
Electronic & Electrical Engineering, decided
to investigate whether images of peoples
noses could be used to recognise
individuals.
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Retinal
the pattern of blood vessels that emanate
from the optic nerve and disperse
throughout the retina depends on
individuals and never changes. No two
retinas are the same, even in identicaltwins.
First the intensity profile is extracted,
then a circular scan is performed to locate
blood vessels.
retinal scan is very difficult to fake
because no technology exists that allows the
forgery of a human retina, and the retina of a
deceased person decays too fast to be used
to fraudulently bypass a retinal scan.
Retinal scanning is part of biometrics, the
field of science and engineering which
develops ways to uniquely identify
individual persons.
the physical aspects of a persons body.
These include items such as fingerprints,
retinal scans, and facial scans. Behavioral
biometric data, sometimes called
behaviometrics, include signatures,
handwriting analysis, and voice pattern
recognition.
Vein, Vascular pattern
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Different part of the body can be used,
generally the hand or the finger.
Blood pulse, cardiac pulse
Recognition using the blood pulse shape
or the electrocardiogram has been
proposed, but there is low activity on this
subject, and this is still a not proven
method.
Reading is performed using the same
material than pulse oxymetry, a infrared
LED and a photodiode, to read the blood
pulse shape.
Skin spectrum
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Lumidigm has established that the
absorption spectrum of the skin depends on
the individuals.
Several LEDs send light at different
wavelenghts into the skin, and
photodiodes read the scattered light,
which is analyzed to perform the
authentication
Dental radiographs
Dental information is used for a long time
in forensics. Dental is not considered as
biometrics because it is not an automated
method, with a (fast) live acquisition of
data. That said, an Automated Dental
Identification System (ADIS, West
Virginia University) is developped
The Michigan state university
(Jain/Chen/Minut) proposes to perform
an automatic authentication based on
dental radiography, using the shape of the
teeth, at the difference of the "simple"
identification used in forensics.
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Ear
Ear recognition uses mainly two features:
canal of the ear which returns a
specific echo
Ear geometry recognition uses the shape
of the ear to perform identification
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An infrared image can be used to
eliminate hair:
Here is a paper about ear shape
recognition using a specific method:
Lips
Lips are not well-known as biometric
features, and not very much studied.
Nevertheless, they are interesting from
several point of views:
Lip prints are know in forensic science
to be different for each individual, as
fingerprints.
Lip movement helps identification
associated with speaker recognition.
Lip shape can be used as a stand-alone
feature to perform authentication
Lip movement
Lip movement recognition is generally
only a sub-system of a combination of
several biometrics, as it is likely that this
feature used stand-alone is not enough to
obtain good accuracy.
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Nail /
Nail recognition is an emerging biometrictechnology, which has not been not very
much studied. Mainly two methods (and two
companies) exist:
Nailbed
The nailbed is an essentially parallel
epidermal structure located directly
beneath the fingernail formed with
parallel lines spaced at intervals. During
normal growth, the fingernail travels over
the nailbed.
Keratin microfibrils within the nailbed
are located at the interface of the nailbed
and the nailplate, or fingernail. Keratin is
a highly birefringent material, so we can
read this structure using polarized ligh
Fingers & Knuckles
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3D Finger surface
Uses the curvature of each small section of
the finger surface, starting from a normal
image
DNA
Although it is the ultimate biometrics
(excepted for twins!) as everyone has DNA,
this is not considered as a biometric
technology because it is not yet fully
automated (and fast).
Biometric Laptop
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For people interested in securing important
computer information, a biometric laptop is
the best choice. Whereas most computers
are protected by one or more passwords,
these laptops require data that is nearly
impossible to hack. Biometric security,
which requires a fingerprint, iris scan or
voice recognition, is a rising phenomenon in
computers. A biometric laptop's added
protection is a nice feature, but its high-tech
security system is not without its problems.
Having a fingerprint reader is the most
prominent type of biometric laptop security.
This is a small window near the bottom of a
keyboard or even embedded in a mouse that
acts just like a scanner, but it scans
fingerprints. Users save fingerprint scans in
a security database and set the security just
like they would for a written password. To
gain control of the computer, the user simply
applies a finger to the scanner, and it reads
the unique traits of that print in order to
grant access.
A less common but equally protective form
of security for a biometric laptop is the iris
scan. This usually involves a small scanner
that is external from the computer. Like the
fingerprint scanner, the user places an eye to
this camera and lets it scan the iris, saving it
to a database within the computer. When the
user wants to start the computer, he or she is
prompted to put an eye to the scanner, and
when the iris matches the database, the
computer will grant the user access. If there
is no match, that person will be denied.
Another form of biometric laptop security is
voice recognition. This feature is the least
common of the three because it is the easiest
to forge. Where the other two take raw
human characteristics, this biometric device
memorizes aspects of a voice's tone, timberand sound. If the user's voice matches the
stored criteria, the security system allows
him or her to use that biometric laptop.
These biometric laptop security features
provide an added layer of security for users,
but they also have problems that simple text-
based passwords do not. The voice
recognition software often does not
recognize the user's speech if they are not
speaking clearly enough, and this can cause
a great deal of frustration. Iris scanners
provide a high level of security but can be
expensive and delicate. Fingerprint scanners
do not memorize the exact fingerprint but
rather a series of points on a print and
therefore are prone to many false negatives,
sometimes preventing the correct person
from gaining access.
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