bio-metrics

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C.U.SHAH COLLEGE OF ENG. & TECH. 1
Guided By Submitted By
G.T.CHAUHAN HARDIK ANIYALI
VIMAL JAVIA
C.U.SHAH COLLEGE OG ENGG. & TECH.
WADHWAN CITY – 363 030

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WADHWAN CITY
DIST : SURENDRANAGAR
CERTIFICATE
This is to certify that Mr. / Ms. ANIYALI HARDIK V.
Mr. / Ms. JAVIA VIMAL M. is / are studying in
Sem – VI of B.E. Information Technology having Roll No. 3 & 15
has / have completed his / her / their seminar on the following topic
successfully.
Topic Name : BIO-METRICS
Staff – Incharge Head of Dept.
(Miss Saroj Bodar)
Date : ___________

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ACKNOWLEDGEMENT:-
We are thankful to our college to give us such opportunity. First of all we are
thankful to Saroj mam. We are also thankful to G.T.Chauhan Sir for providing us proper
guidance. Thanks are also due to Mitesh Sir for supporting us.
We are also very much thankful to our parents who encourage us and always
giving us the strong support.
Hardik Aniyali
Vimal Javia

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ABSTRACT:-
Bio-metrics is modern security system. It uses a person’s biological features to give
access rights. The biological features like finger print, voice print, iris pattern, face print,
signature(dynamic), retina, hand geometry, ear form , DNA, odor, keyboard stroke,
finger geometry, vein structure of back of hand etc. are used. So, in this any
unauthorized person cannot trap the information or assets. Today, to prevent illegal
operations this technique is widely used. It is a user-friendly technique, which is
accepted by almost all fields.
The problem of the personal identification has become a great matter in today’s world.
Biometrics, which means biological features based identity recognition, has provided a
convenient and reliable solution to this problem. This recognition technology is relatively
new with many significant advantages, such as speed, accuracy, hardware, simplicity and
applicability.
Biometrics is a means of identifying a person by measuring a particular physical or
behavioral characteristic and later comparing it to a library of characteristics belonging
to many people. Biometric systems have two advantages over traditional ID methods.
First, the person to be identified does not have to present anything but himself. Second,
the critical variable for identification cannot be lost or forged. Retinal identification is
the most accurate of the biometric methods used at this time. It will replace traditional
ID methods such as P.I.N. numbers for accessing A.T.M.s and virtually every other
electronic device used for conducting business where identification is a requirement
and prerequisite.After the arrival of IT(Information Technology) this technique is used
along with computer and this embedding gives the perfect result.
Contents:- page-no:-
1) Brief on Security System 1
2) Introduction to Bio-metrics 2
3) A Few Defination 3

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4) History of Bio-metrics 4
5) International Bio-metrics society 5
5.1 Purpose
5.2 Journal
5.3 Meetings
5.4 Biometrics Bulletin
6) Generic model of bio-metrics 6
6.1 Data Acquisition:-
6.2 Transmission: -
6.3 Signal Processing:-
6.4 Decision Making:-
6.5 Data Storage:-
7) Phases of Bio-metrics 8
7.1 Input
7.2 Process
7.3 Output
8) Bio-metrics Identification 10
8.1 Voice Print
8.2 Finger Print
8.3 Iris Pattern
8.4 Face Print
8.5 Hand Geometry
8.6 Retinal Scan
8.7 Keystroke Dynamics
8.8 Facial Recognition
8.9 Signature Recognition
9) Captured Using Web Cam and Microphone 19
10) Comparision of Bio-metrics technique 20
10.1 Uniqueness of biometric features
11) How well do Bio-metrics works? 23
11.1 False Accept Rates
11.2 False Reject Rates
11.3 Equal Error Rates

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11.4 Validity of Test Data
12) Is DNA Bio-metrics ? 25
12)About Bio-metrics 26
13.1 Will Bio-metrics solve all security concerns ?
13.2 Which is the best identification technique ?
13.3 Is Bio-metrics more ‘secure’ then password ?
13.4 Applications
13.5 New Opportunities
13.6 Future Technology
13.7 Benefits
15) Conclusion 30
16) Reference 31
1. WHAT SECURITY ? WHY SECURITY ?
 From the beginning of the human culture, people are always trying to secure their
properties. Because some people are always eager to snatch others properties.
 Security refers to prohibit some unauthorized persons from some important data
or from some precious assets.
 To restrict this kind of theft human beings are making special systems that can
prevent the thieves such systems are known as security systems.

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 We can consider the starting of these kinds of systems through lock and key.
 A Frenchman Alexander Fish has made a strong, fire proof safe in 1844. And
Linas Yel –an American, has invented a Pin lock kind of lock. Both these
equipments are used to provide security to money, important documents and
jewellary. So this is the first step in the world of security system.
 At that point of time this arrangement for security was considered the best. But as
time passes it was found that any unauthorized person could access these through
duplicate keys or using any technique. So as the world progresses, the thieves
become more intelligent to break the security.
 Thus, we always need a new and strong security system to protect our assets.
 So, security system is ever developing field.
 Today in the world of e-commerce and Internet this thing is becoming more and
more important because today the world is like village, from anywhere, any time,
any body can harm you.
e.g. :-If you are purchasing something from web and because of
lack of security someone come to know your bank account
number. Then that person will have all the information of your bank
account, which can perhaps put you in a big trouble!
 Now a days, there are many security systems are available. But we shall
concentrate on ‘BIO-METRICS’.
2. INTRODUCTION
BIO=Pertaining to biology; MATRICS=Science and art of measurement.
o The term 'biometrics' is used to refer to any and all of a variety of
identification techniques which are based on some physical and difficult-
to-alienate characteristic.
o Today, the science of biometric technology refers to the "automated"
methods used to recognize a person based upon physiological or
behavioral characteristics.

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o Biometric technologies are becoming the foundation of an extensive array
of highly secure identification and personal verification solutions.
 Biometrics is a modern technological field that focuses on identifying an
individual through his or her unique physical traits.
 A biometric is a measurable, physical characteristic or personal behavioral trait
used to recognize the identity or verify the claimed identity of an enrolled user.
 Biometrics is automated methods of recognizing a person based on a
physiological or behavioral characteristic.
Physiological techniques include fingerprint recognition, retinal and iris
scanning, facial recognition, hand and finger geometry and DNA analysis.
Behavioral techniques include handwriting recognition, voice or speech
recognition, gait, and keystroke dynamics.
 In all automated systems, the fundamental operational steps are:
1. Capture: The biometric data is captured, digitized and entered into a database.
2. Extraction: A template is created using this measurable unique data.
3. Comparison: The template is compared with a new sample.
4. Match/Non-Match: The existing template matches the new sample or it does not.
 The goal of most automated biometric ID systems is one of two outcomes:
1. Verification: Is the person who the they claim to be?
2. Identification or recognition: Who is this? Is the person already known to the system
under a different identity?
“Only biometrics can identify you as you [Not Password].”
3. A FEW DEFINATION
 Biometrics Authentication
Person authentication or simply authentication is a task of confirming or denying
a person’s claimed identity. Biometrics is a measurement using a person’s behavioural or
physiological characteristics. Examples of these characteristics are fingerprints, face,
voice and signature. Biometric authentication is a task of confirming or denying a
person’s claimed identity using his behavioural or physiological characteristics.

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 Biometrics, Biometric or Biometry
Biometry refers to a much broader field involving application from statistics to
biology and medicine. Biometrics is a noun and biometric is an adjective.
Note the distinction between the terms biometrics and biometry. Biometry refers to a
much broader field involving application from statistics to biology and medicine.
Biometrics is a noun and biometric is an adjective.
 Authentication versus Identification
According to [Jain, 1999], associating an identity with an individual is called
personal identification. This problem can be categorised into: (i) authentication and (ii)
identification. Authentication refers to the problem of confirming or denying a person’s
claimed identity while identification refers to the problem of establishing a subject’s
identity. The differences between identification and authentication can be summarised in
Table A.1.
Table A.1 Identification versus authentication
Identification Authentication
It determines the identity of the person. It determines whether the person is indeed
who he claims to be.
There is no identity claim from the user.
The system has to search through its record
to find the identity. This search is called a
many-to-one mapping. The cost of
computation in the identification task
increases in proportion to the number of
record of users.
The user makes an identity claim. By using
the claim as a key, the system searches the
user’s record to compare. It is a one to one
mapping. The system uses the identity as a
key to call for the identity’s record. The
cost of computation is not dependant on
the number of record of users.
It is often assumed that a captured
biometric signature comes from a set of
known biometric feature stored in the
system. This is referred to as closed-set
identification.
The captured biometric signature comes
from a large set of unknown users. This is
referred to as open-set verification.
4. HISTORY OF BIO-METRICS
 Francis Galton is one of the founders of Bio-metrics. In 1892, Galton
invented the first system of fingerprinting.
 He has observed that No two persons have same finger print. Each and
every person has got a unique finger print pattern.

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 In 1968, Bio-metrics technique was implemented successfully when well-known bank
of New York has arranged the finger print scanning to access the currency walt , first
time in the world.
 But after 1990, when IT (Information Technology) comes into the picture, through its
advancement and simplicity Bio-metrics technique becomes very popular.
 This new technology is very easy to understand compare to its heavy label.
Because of user-friendly environment this technique is very well welcomed by
various fields.
5. THE INTERNATIONAL BIO-METRICS SOCIETY
The International Biometric Society, founded in 1947, is an international
organization for the advancement of the subject-matter sciences through the development
of quantitative theorgies and the development, application, and dissemination of effective
mathematical and statistical techniques.
5.1 Purpose
To this end, it welcomes to membership biologists, statisticians, and others
interested in applying statistical techniques to research data. The International

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Biometric Society and its journal, Biometrics, serve as an invaluable means of
communication between the subject-matter specialists and the statisticians.
5.2 Journal
Biometrics is published quarterly. Its general objectives are to promote and extend
the use of mathematical and statistical methods in the various subject-matter
disciplines, by describing and exemplifying developments in these methods and
their application in a form readily assimilable by experimenters and those
concerned primarily with analysis of data. The journal is a ready medium for
publication of papers by both the experimentalist and the statistician. The papers
in the journal include statistical, authoritative expository or review articles, and
analytical or methodological papers contributing to the planning or analysis of
experiments and surveys, or the interpretation of data. Many of the papers in
Biometricscontain actual worked examples of the statistical analyses proposed.
5.3 Meetings
Encouragment is given the subject-matter experimenter by holding symposia
dealing with applied statistics as a part of annual meetings of the biological,
chemical, engineering, and physical science societies. Such symposia afford an
opportunity for subject-matter specialists and statisticians to discuss problems of
mutual interest. At Regional meetings of the Society, a member is afforded an
opportunity to present technical papers. This permits the exchange of ideas and
information through formal presentation and informal contacts with fellow
statisticians and experimentalists.
5.4 Biometric Bulletin
The International Biometric Society also publishes an informal newsletter
containing news about membership activities, letters to the editor, and membership
and editorial commentaries. It is a means for expressing ideas on a wide range of
statistical and biometrical matters and is also published quarterly.
6. GENERIC MODEL OF BIO-METRICS

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6.1 Data Acquisition:-
Data collection involves use of sensors to detect & measure an individual’s
physiological or behavioral characteristics. The biometric feature must have the
following characteristics:-
(a) Universality, which means that every person should have the characteristic,
(b) Uniqueness, two persons should not have the same term or measurement of
characteristic,
(c) Permanence, the characteristic should be invariant with time,
(d) Measurability, the characteristic can be quantified that is the origin of the
Cameras used in biometric systems are generally either CCD(charge couple device) or
CMOS(combined metal oxide semiconductor) image sensors.CCD’s are comparatively
more costlier than CMOS. The cost of CCD is nearly 2500 Rs. And CMOS is about 800
to 1000 Rs. Price depends on the resolution which reflects the accuracy of biometric
system.
6.2 Transmission: -
Not all the biometric systems process and store data on the measuring device.
Often measurement is made using relatively simple device to a computer or server for
processing and/or storage. Depending on the system, the data may be relatively large
and thus would need to be compressed for quick transfer. The compression algorithm

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needs to be selected carefully; otherwise it may introduce some artefacts that could
impact the decision process.
In any image scanning Biometric system, JPEG compression is preferred due to
the blockness it produces at high compression ratios. The data can also be transmitted
to the database for storage as raw data.
6.3 Signal Processing:-
The signal processing unit uses features extraction algorithms to extract true
biometric information from the sample in presence of noise introduced during data
collection and transmission. Additional measurements are made if any flaw or
corruption is noted, to ensure good quality.
Pattern matching involves comparing the feature sample to a stored sample.
(The biometric data can be stored locally on the biometric data can be stored locally on
the biometric device, some central database/server, or on a smart card issued to users.)
The result of the comparison is sent to the decision system to determine the match.
6.4 Decision Making:-
The final step is the decision to accept or reject user, and is based on a security
threshold. The threshold value is either a parameter of comparison process itself, or the
system compares the resulting match value with the threshold value. If for example, in
a system performing identity verification, the match value is equal to or higher than the
threshold value, the user is accepted. In an identification system, acceptance might
require a match value that is both higher than threshold value and higher than the
second-best match by a specific amount.
6.5 Data Storage:-
After extracting the biometric features, the system stores and maintains the new
master template. Choosing proper discriminating characteristics for categorizing
records can facilitate future searches. The system stores the templates in one of four
locations: a card, a server’s central database, a workstation, or an authentication
terminal. If privacy is a concern, a card is the only choice because sensitive biometric
data should not be stored (and potentially misused) in a central database.
7. PHASE OF BIO-METRICS
7.1 Input
 Using appropriate input device it will collect the data of the person’s
biological features. These features are known as the master key for

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the computer.
 Let us put in a simple manner.
For recording and converting biometric traits to usable computer data, one needs an
appropriate sensor (see table). Of course, costs can greatly vary for different sensors.
However, we can't forget that many technical devices already have sensors built in, and
therefore, offer possibilities to measure biometric features nearly free of cost.
Biometric Trait Sensor
Fingerprint (Minutia) capacitive, optic, thermal, acoustic, pressure
sensitive
Signature (dynamic) Tablet
Facial Structure Camera
Iris pattern Camera
Retina Camera
Hand geometry Camera
Finger geometry Camera
Vein structure of the back of the
Hand
Camera
Ear form Camera
Voice (Timbre) Microphone
DNA Chemical Lab
Odor Chemical sensors
Keyboard Strokes Keyboard
Comparison: Password Keyboard
7.2 Process
 Processes the input data. Here, computer takes the measurement of inputed
Biological features.
 No two persons have same finger print. So, computer joins the points of that finger
print features and make the pattern of it and it will store that pattern into its memory.
Then computer compares this pattern against the master keys.
 e.g.: - Putting the tracing paper on Indian map, if we join Banglor,
Chennai, Delhi, Hyderabad, Mumbai, Nagpur, Ahmedabad, Jaipur and
Lukhnow drawing a line then by chance the original map is lost. Now
if we want to know the distance between Ahmedabad and Bhavnagar
for that we require the original one, which is drawn with the same
measurement. But In this case, actual map is lost so we are helpless.
Similarly, the finger print used by the computer to make its pattern is
deliberately hidden. Thus, the security system does not allow any
unauthorized person.

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7.3 Output
 Testing of processed data and give the access rights to the person. Here,
When any person scanned his/her finger print , computer will
store a Bio-logical featured pattern and compares it against the stored master-
key in its memory. And if it is matched, then permission granted else not.
8.BIO-METRICS IDENTIFICATION
CONVENTIONAL METHODS OF BIOMETRIC IDENTIFICATION ARE……….
1 VOICE PRINT
2 FINGER PRINT
3 IRIS PATTERN
4 FACE PRINT

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5 HAND GEOMETRY
6 RETINAL SCAN
7 KEYSTROKE DYNAMICS
8 FACIAL RECOGNITION
9 SIGNATURE RECOGNITION
8.1 VOICE PRINT: -
 In this world of bio-metrics the first invention is of voice print.
 Voice recognition is very different to speech recognition. Speech
recognition detect words and sentences from an incoming audio signal
whereas voice recognition tries to detect the speaker given a voice
sample.
 Here voice is recorded by microphones.
 But as each & every person has got different voice pattern that’s why
no two voice prints are matched.
 Voice print is determined by many different factors: size of the vocal
cavities (throat, oral, nasal) as well as the characteristics of the vocal
chords themselves.
 Your voice is further modified by the way you speak - the way your
mouth, lips, tongue, jaw and teeth move (these are called articulators).
Therefore, the chances of two people have the same vocal
characteristics are minute.
 But this technique is not 100% authentic because of the following
reasons.
 Each and every person’s voice changes as per the mood.
 All microphones, which are used to fetch the voice, may not
work properly.
 During the recording of voice if there is any background sound
or noise then it will not be able to give perfect result.
 The computer converts the voice pattern into 0 & 1.After taking the
input that input is also converted into 0 & 1.If the both code matches
the person is authorized.
8.2 FINGER PRINT: -

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 In this technique, no two persons have the same
finger print, Francis Galton proves this after a long observation in
1892.
 No ID Card is as best as finger print because the possibility of
matching two person’s finger print is 0%.
 Finger print is also called finger scanning.
 To scan the finger print, a special kind of scanner that can work with
optical rays is used.
 When a person put his/her finger on the transparent glass of scanner
,CCD chip scans the biological features of finger.
 It fetches the diagram of finger print & delivers it to the computer
where a special programme measures the distance between the special
features & that print.
 Here, those special features are core, split, island, end & delta.
 The new sophisticated software of bio metrics scans the finger as well
as palm.
 In this case, it takes the 90 types of measurement of palm & matches
that new digits against the stored digits in the computer’s memory as
well as finger print is matched & then it gives the access rights.

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 Hand technology is similar but surprisingly uses smaller amount
information. Hand technology is also susceptible to injuries to hand
and can be fairly expensive to install.
 Most fingerprint data takes up around 250Kb.
 Fingerprinting is a widely used and accepted technology with very
good accuracy rates.
 Thus this technique is more authentic than the voice print.
 The computer converts the finger pattern into 0 & 1.After taking the
input that input is also converted into 0 & 1.If the both code matches
the person is authorized.
8.3 PATTERN OF IRIS: -
 an iris has a mesh-like texture to it, with numerous overlays
and patterns. The iris is located behind the cornea of the eye, but in
front of the lens. Its only physiological purpose is to control the
amount of light that enters the eye through the pupil, but its
construction from elastic connective tissue gives it a complex,
fibrillous pattern.
 Iris recognition is the epitome of biometric identification - the

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 entire planet could be enrolled into an iris database and there would
still be a minute chance of false identification or rejection. In finger
print technique there are only 90 special features, but in iris pattern
there are 266 special features.
 In 1998, Dr. John Daugman. -inventor of Cambridge University of
Britain has compared the approx 3,00,00,000 the iris but he couldn’t
find at least one similarity.
 In this technique CCD camera, which looks like small camcorders,
scans the eye’s iris pattern.
 The iris pattern of a person’s left and right eyes are different.
 Here, CCD scan either left or right eye’s iris pattern.
 After scanning that pattern is delivered to the computer’s processing
unit.
 Computer only considers the data of iris and removes other data and
analyzes the total 266 features and assigns a particular value to each
feature.
 The pattern of iris is converted into the total 4,096 bits of 0 & 1.
 Then computer compares the new data of 0 & 1 to the iris print stored
as master key and if it is matches then gives the access rights.
 Iris has stable and distinctive features for personal identification. That
is because every iris has fine and unique patterns and does not change

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over time since two or three years after the birth, so it might be called
as a kind of optical finger print
 The Iris Code is so specialized that the chances of two irises having
the same code are 1 in 1052
!
 SOME CURRENT AND FUTURE APPLICATIONS OF IRIS
RECOGNITION:
 Secure accesses to bank cash machine accounts:
The banks of United, Diebold and Sensar have applied it. After
enrolling once (a “30 ”second process), the customers need only
approach the ATM, follow the instruction to look at the camera, and be
recognized within 2-4 seconds. The ultimate aim is to provide safe and
secure transactions.
 Ticket less, document-free air travel:
Passengers and airline employees will store digital images of
their irises on a database. After the image of your iris is on the file, a
video camera will be able to instantly verify your identity and clear
you to board the aircraft.
 Computer login: the iris an living password.
 National border controls: the iris as a living passport.
 Premises access control (homes, office, laboratory).
 Credit card authentication.
 Secure financial transactions.
 Internet security.
8.4 FACE PRINT: -
 Facial biometrics use various features of the face to recognize or verify a
user.
 Fourth type of biometrics identification is of face print.
 To capture face print of any person special kind of camera is used.
 This vide camera delivers the capture image to compute

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 Computer make a pattern of that image using a software .
 To make this pattern it will use approx 50 features of face like the distance
between two eyes, breath of nose, cheeks, area of forehead, jaws etc.
 These features are converted into digital form.
 Though it is not necessary that a high –tech and sophisticated software
identify proper person.
 The computer converts the face pattern into 0 & 1.After taking the input
that input is also converted into 0 & 1.If the both code matches the person
is authorized.
 Here are some possibilities.
 To create a pattern of a person’s face, the face of the person must
be within the range of 35 degrees.
 A camera cannot recognize a person wearing goggles.
 e.g.: During a testing at Palm Beach, America, the camera has
recognized simultaneously two persons as culprit. The face of one
of them is really stored into the computer software as culprit. For
that person Bio-metrics technology has been proved 100% true.
While according to plan other person is eating a Jellybeans candy
and he acts as if he is blowing. By doing this face was looking
quite similar to the first one. So, camera recognizes him as a culprit
by ringing an alarm.
 Because of continuous movement of head camera cannot recognize
the face.
 In short, in compare to finger print and iris pattern -face print is
less authentic. In some circumstances this is very useful like when
we caught the culprit and make him/her to stand against the
camera.
 A software FaceIt can compare 6,00,00,000 photos against the
face/minute.
 In this process there is no chance of any error. But we cannot relay
on it completely. Because of Bio-metrics the human body is
serving s mobile lock and key.

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8.5 Hand Geometry: -
Hand geometry is by far the most widely used
biometric system. The ID3D Hand key system from
Recognition Systems, Inc. is the most popular.
Various methods are used to measure the hand; these
methods generally fall into one of two categories :
1. Mechanical
2. Image-edge detection
Either method produces estimates of certain person.
Key measurements of the hand (length of fingers and thumb,
widths, etc.); this data are used to "categorize" a person.

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It works as follows:
The user first enters a PIN number on a keypad, and then
positions their hand on a plate using a set of guidance pins which
ensures that the hand will be in generally the same position for every
measurement. Then a digital camera mounted above the plate, with
the aid of a mirror, takes a picture of the top and side views of the
hand. The dimensions of the hand, such as finger length, width and
area, are extrapolated from the image and the magnification of the
camera. This system, however, is subject to an attack using a fake
hand modeled after that of an authorized user.
8.6 Retinal Scan: -
Retinal Scan technology is based on the blood vessel pattern in the retina of the
eye. A retinal scan can produce almost the same volume of data as a fingerprint image
analysis.
It works as follows:
The user positions their head against a support, and a low power infrared light is
directed against the back of the retina. The image of the pattern of veins is reflected back
to a camera.
8.7 Keystroke Dynamics: -
This method analyzes the way in which a user types at a computer keyboard. The
input is monitored thousands of times a second, and the durations of keystrokes and the
latencies between them are recorded.
The goal for keyboard dynamics is continual authentication of the user while at a
computer; so that if an intruder user had access to the users session while they were
away, the machine would eventually be able to recognize the discrepancy. Even though
typing patterns are behavioral characteristics, they are very hard to mimic.

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8.8 Facial Recognition: -
Facial recognition technology has recently developed into two areas of study:
1. Facial metrics
2. Eigenfaces.
Facial metrics technology relies on the measurement of specific facial features
(e.g., the distance between the inside corners of the eyes, the distance between the outside
corners of the eyes and the outside corners of the mouth, etc.) and the relationship
between these measurements. Within the past two years, an investigation has been made
into categorizing faces according to the degree of fit with a set of "eigenfaces". It has
been postulated that every face can be assigned a "degree of fit" to each of 150
eigenfaces; further, only the template eigenfaces with the 40 highest "degree of fit" scores
are necessary to reconstruct a face with over 99% accuracy. The difference between the
eigenface method of facial categorization and the police artist method of building a face
from template parts is that the eigenface method is based upon an actual photo of the
individual and the "eigenface" information is derived from a computer-based analysis of
the digital image of the photo. Eigenfaces are (reportedly) highly repeatable and are not
affected by human subjectivity. Eigenface technology has some promise, but it is a
technique that is just in the infancy stage of development. Very little data regarding
eigenface error rates (false negative, false positive) exists at this point.
8.9 Signature Recognition: -
Signature recognition is based on the dynamics of making the signature, i.e.,
acceleration rates, directions, pressure, stroke length, etc., rather than a direct comparison
of the signature after it has been written. The problems with signature recognition lie
in the means of obtaining the measurements used in the recognition process and the
repeatability of the signature. The instrumentation cannot consistently measure the
dynamics of the signature. Also, a person does not make a signature in a fixed manner;
therefore, the data obtained from any one signature from an individual has to allow for a
range of possibilities. Signature recognition has the same problem with match
discrimination (i.e., finding a match in a large database) as does hand geometry.

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9.Biometrics Captured Using Web Cam and Microphone
Figure 1 is made up of images of 320240 pixels. Figure 1(a) is the typical
upright front image that we captured before processing it. At 50mm, the shortest depth-
of-field, we can capture eye at a resolution of 320240, as shown in Figure 1(b). By
visual judgement, this is quite promising for the authentication purpose, when lighting
and reflection can be controlled. Since all eyes are round, colour analysis becomes an
important property for extraction.
(a) (b)
(c) (d) (e)
Figure 1 : Biometrics captured by the WebCam in this project
Figure 1(c) shows an ear. An ear has more structure thus creates different shading.
Segmenting ear can be very challenging. However, if ear can be segmented reliably and
represented in a canonical image space, it is possible to extract ear shape information.
The same goes to fist as shown in Figure 1(d). We tried to capture thumb too in the hope
that fingerprints might be observed. However, at such resolution, fingerprints are partially
captured and is not clear.
By visual judgement, we have decided to use face biometrics, over eye
biometrics, ear and fist in decreasing order of priority.

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10.COMPARISON OF BIO-METRICS TECHNIQUE
10.1 Uniqueness of biometric features
Table shows the cross accuracy of different biometrics.
Table : Comparison of Biometrics Techniques [Ruggles, 1998]
Biometrics Crossover Accuracy
Retinal Scan 1:10,000,000+
Iris Scan 1:131,000
Fingerprints 1:500
Hand Geometry 1:500
Signature Dynamics 1:50
Voice Dynamics 1:50
Crossover accuracy is the ratio of the crossover frequency as compared to the
whole population of test data. The smaller the crossover accuracy, the more unique the
biometrics is. It should be noted that comparison across biometrics is by no means
measurable. Even the quality of same biometrics is difficult to judge unless the results are
tested on the same data set. [O’Gorman, 1999]. Therefore, sufficient bias is expected
from the readers as well.
From Table 2, Retinal scan, after [Daugman, 1995], appears to have the highest
crossover accuracy. Even though Iris scan has high cross over accuracy, its user
acceptability is low. Fingerprints and hand geometries are equally “unique”.
Signature dynamics and voice dynamics have the lowest accuracy rates according
to [Ruggles, 1998]. In addition, these two techniques rely on behavioural measurements
as opposed to physical measurements. In general, behavioural biometrics is less reliable
than physical biometrics.
Retinal scan has high accuracy but also has a high data collection error rate and
low user acceptability. For this reason, retinal scan exists only in science fiction movies
but not in real life applications!
The fingerprint biometric has a low data collection error rate and high user
acceptability. Further, fingerprint technology has had the most research and development
money applied to both identification and authentication problem. Finally, fingerprint
biometrics has the highest acceptance in the identification community and virtually every
large biometrics system in operation today uses fingerprint biometrics. Notwithstanding
it's association with "criminal" applications, fingerprint biometrics is generally accepted
by clients.

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The chosen biometrics in this project, i.e., face and voice, are based on user
acceptability and another important factor, the availability of resources in the laboratory.
Once the system is established, moving into other biometrics would be easier.
Table 3 : Comparison of biometrics technologies based on perception of three biometrics
experts according to [Jain, 1999]

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11.HOW WELL DO BIOMETRICS WORK?
11.1 FALSE ACCEPT RATES
11.2 FALSE REJECT RATES
11.3 EQUAL ERROR RATES
11.4 VALIDITY OF TEST DATA
Biometric devices can be adjusted to favor security or user convenience. How
well do Biometrics work? Is depending on four points.
11.1 False Accept Rates
 The probability that a biometric device will allow an
unauthorized person is called the "False Accept Rate”.
 False Accept Rates claimed for today's biometric access systems range
from 0.0001% to 0.1%.
 It's important to remember that the only way an unauthorized person
can get access is if a unauthorized person tries. Thus, the False Accept

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Rate must be multiplied by the number of attempts by unauthorized
person to determine the number of possible occurrences.
11.2 False Reject Rates
 The probability that a biometric device won't recognize an authorized
person is called the "False Reject Rate”.
 The False Reject Rates quoted for current biometric systems range
from 0.00066% to 1.0%.
 A low False Reject Rate is very important for most applications, since
users will become extremely frustrated if they're denied access by a
device that has previously recognized them.
11.3 Equal Error Rates
 The point where false accept and false reject curves cross is called the
"Equal Error Rate”.
 Error curves give a patternical representation of a biometric device's
"personality."
 The Equal Error Rate provides a good indicator of the unit's
performance. The smaller the Equal Error Rate, the better.
11.4 Validity of Test Data
 Here, it checks for validity of the processed data and decides whether
the person is authorized or not.
 Testing biometrics is difficult, because of the extremely low error rates
involved. To attain any confidence in the statistical results, thousands
of transactions must be examined.
 It's important to remember that error rates are statistical: they are
derived from a series of transactions by a population of users.
 In general, the larger the population and the greater the number of
transactions, the greater the confidence level in the accuracy of the
results.

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 If the reported error rate is 1:10, then a sample of 100 transactions may
provide a sufficient confidence level. Conversely, a 100-transaction
sample would be too small if the error rate was reported as 1:100,000.
Biometric devices are extremely secure, thanks to the combination of low False Accept
Rates at moderate sensitivity settings, combined with a short user keypad code.
At the same time, biometrics are extremely convenient and error-free, thanks to low False
Reject Rates.

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12.IS DNA A BIOMETRIC?
DNA differs from standard biometrics in several ways:
DNA requires a tangible physical.
DNA matching is not done in real-time, and currently not all stages of
comparison are automated.
DNA matching does not employ templates or feature extraction, but rather
represents the comparison of actual samples.
Regardless of these basic differences, DNA is a type of biometric inasmuch as it
is the use of a physiological characteristic to verify or determine identity.

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13.ABOUT BIO-METRICS
13.1 WILL BIO-METRICS SOLVE ALL SECURITY CONCERNS?
13.2 WHICH IS THE BEST IDENTIFICATION TECHNIQUE ?
13.3 IS BIO-METRICS MORE ‘SECURE’ THEN PASSWORD?
13.4 APPLICATION
13.5 NEW OPPORTUNITIES
13.6 FUTURE TECHNOLOGY
13.7 BENEFITS
13.1 Will Biometric Solve All Security Concerns?
 No System Can be 100% Safe
 Biometric Measures Can be Very Successful in Fighting Today's Security
Concerns
 Major Drawback in Adopting Biometric Systems is that Concerned person
Need to be Physically Present
13.2 Which is the best technique among above ?
Accordingly, the pattern of iris is the best one to recognize a person. Because the
possibility of two persons having the same iris pattern is 1 per 1000 million , the
population of earth is 6 million so eyes are 12 million and that is why probability is not
at least 1%.
13.3 Is Bio-metrics more "secure" than passwords?
This question at least poses two problems: biometrics is not equal to biometrics, and the
term "secure" is in fact commonly used, but it is not exactly defined. However, we can try
to collect pros and cons in order to find at least an intuitive answer.
It is a matter of fact that the security of password protected values in particular depends
on the user. If the user has to memorize too many passwords, he will to use the same

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passwords for as many applications as possible. If this is not possible, he will go to
construct very simple passwords. If this will also fail (e.g., if the construction rules are
too complex), the next fall-back stage is to notify the password on paper. This would
transform "secret knowledge" into "personal possession". Of course, not every user will
react this way. Rather the personal motivation plays an important role: is he aware of the
potential loss caused by careless handling of the password? It is easy if the user is the
owner. But often foreign possession (e.g., that of the employer) has to be guarded, whose
value one often can hardly estimate. If motivation is missing, any password primarily
tends to be felt bothersome. In this case, and that seems to be the normal case, it is
assumed that biometrics has considerable advantages.
Contrariwise, passwords feature an unbeatable theoretic protection ability: an eight-digit
password which is allowed to contain any symbol from an 8-bit alphabet offers 1020
possible combinations! This is a real challenge for any biometric feature. The
requirements are obvious: such a password is maximally difficult to learn, it must not be
written down, it must not be passed to anyone, the input must take place absolutely
secret, it must not be extorted, and the technical implementations must be perfect. This
leads us to the practical aspects: the implementation must be protected against replay
attacks, keyboard dummies (e.g., false ATMs), wiretapping etc. Even biometric features
have to cope with such problems. However, it can be assumed that the protection of
biometric feature acquisition is not easier than the acquisition of the password, provided
the implementation expense is comparable!
13.4 Where BIO-METRICS is used?
 For Security
 Protect Sensitive Data
 High degree of identity certainty in transactions
 Create databases with singular identities
 For Accountability
 Improve auditing / reporting / record keeping
 Time keeping
 For Efficiency
 Reduce password-related problems
It is also used in following areas.
 Enterprise-wide network security infrastructures
 Secure electronic banking, investing and other financial transactions
 Retail sales

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 Law enforcement
 Health & Social services
13.5 The New Opportunities For Biometrics
 The unfortunate events of September 11,2001 have placed the recent focus on
creating new systems and installations employing biometrics.
 Examples include facial recognition at airports and fingerprint and iris scanning
solutions at new government facilities.
 Combination of Biometrics with smart cards
 Smart cards, when combined with biometrics, offer a number of benefits.
o smart cards provide a portable storage mechanism for the biometric
template. This means template management is eliminated across the
biometric reader network. Enrolled users present their smart card to the
biometric reader at any location where the card is valid. The biometric
template stored on the card (which is usually encrypted) is compared to
the live biometric. If the two match, the system grants the user access.
o Another benefit of combining biometrics with smart cards pertains to dual-
technology cards that are embedded with a smart chip. These combination
cards function as both smart cards and proximity cards. This grouping
permits organizations currently using proximity-based access control to
incorporate biometric security and limit card issuance to users who are
permitted access to the biometrically secured area.
o Lastly, since the biometric templates are stored on individual cards, the
number of users for any particular biometric reader is unlimited. This
scenario differs from biometric readers that store the template, thereby
limiting the template capacity to the reader's storage capacity.
13.6 Near Future Technologies
 In near future every person having a Bio-chip in the body.
 This Bio-chip concept is recently used in an African Safaris to trap the activities
and diseases of animals. For this every animal has a Bio-chip in its body.
 For Bio-chip in human we will store identification information.

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 So, in future it may not require to ask “What is your name?” just make a shake
hand and allow the Bio-chips to interact and will know the person’s
Identification.
 We don’t know, But Bio-metrics identification may include brain Chemistry
because every one has got different brain chemistries.
 Nowadays, a ‘Bio-Processor-chip’ is available which can recognize the bacteria
that can cause diseases- spread through blood, saliva
and urine in few minutes instead of hours.
13.7 Benefits of Adopting Biometrics
 No Need to Remember Passwords:
As it uses our biometry we are not supposed to give any password.
Because where ever we go our finger print, iris pattern, our face, voice
definitely with us!
 Unauthorized Access to Personal Data Can be Prevented:
It is a one type of security system that no one can hack it because they
do not have our fingerprint, iris,voice,face etc. So, it prevents the data from an
unauthorized person.
 Fraudulent Use of ATMs, Credit Cards Can be Prevented:
None can use our ATM just by knowing our PIN. Because no number
or password is there.

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14. CONCLUSION :-
We conclde that for biometrics is better technique for any security. This technique is
improve then unauthorized person can not access any thing our assets. It depends on
physical behavior. This technique is possible only on the man identification not its
document needed for it.

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15.REFERENCES:-
1. SAFARI [June 2003 {Issue No.114}]: - The Monthly Magazine
2. www.findbiometrics.com
3. www.howstuffworks.com
CONCLUSION :-
We conclde that for biometrics is better technique for any security. This technique is
improve then unauthorized person can not access any thing our assets. It depends on
physical behavior. This technique is possible only on the man identification not its
document needed for it.

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