Essay: An overview of the various biometric approaches


A Biometrics system is actually a pattern recognition system that utilizes various patterns like iris, retina and biological traits like

fingerprint, voice recognition, facial geometry and hand geometry etc. What makes Biometrics really attractive is that the various

security codes like the passwords and the PIN can be interchanged between people but the physiological traits can’t be. However,

the misuse and theft of these security measures are also on the rise. To overcome from such problems we have a new solution i.e.,

ECG pattern matcher. This paper gives the overview of key biometric technologies and basic techniques involved followed by the

uses, benefits and drawbacks. The various opportunities for ECG are mentioned.

Key Words: Biometric, biometric security system, biometrics concerns, recognition methods, identification, access

control, facial recognition, fingerprint reader, voice recognition, iris/retinal recognition, vein recognition, DNA

recognition, privacy, safety.



Biometrics for authentication: Biometrics traits are the

strongest link between a person and his identity as it cannot

be easily shared, lost or duplicated. Hence it is more

resistant to social engineering attacks. This type of system

requires user to be present at the time of authentication. It

can deter user from making false claims. Hence it can be

incorporated in security applications.

Law enforcement agencies in world rely on fingerprints for

criminals and forensic identification. Biometric traits deal

with access control, checking for multiple access control,

international border crossing and secure identification

documents. Each biometric trait has its own advantages and

weak points. The technique of using biometric methods for

identification can be widely applied to forensics, ATM

banking, communication security, attendance management

systems, and access control. It also plays an important role

in enhancing homeland security.

Biometric techniques involve ‘metrics’ or measurements of

some kind, rather than depending merely on familiar or

hidden methods [8].

Taxonomy of Biometric Techniques given below:

‘ Appearance – These are the physical descriptions

like color of skin or eyes, texture of hair, gender,

race, physical markings, height and weight.

‘ Social behavior -these features correspond to style

of speaking, habituated actions and visible


‘ Bio-dynamics – the way in which a person signs,

rhythm of speaking, keystroke dynamics,

particularly in relation to login-id and password.

‘ Natural physiography ‘These include patterns of

fingerprints, hand geometry, retina, iris, DNA,

earlobes and many more.

‘ Imposed physical characteristics like dog-tags,

collars, bracelets and anklets, bar-codes, embedded

micro-chips .[8]


Biometric System: Biometric system is a computer that

implements biometric algorithms and makes use of sensing,

feature extracting and matching modules. The sensing part

captures the traits, feature extraction is done to eliminate


Volume: 03 Issue: 01 | Jan-2014, Available @ 1

IJRET: International Journal of Research in Engineering and TechnologyeISSN: 2319-1163 | pISSN: 2321-7308

unnecessary information and the matching modules match

the traits with the references stored in the database. There

are two stages in the authentication process. They are the

enrollment and verification. Enrollment is the process of

storing the traits in the database and verification the process

of matching the extracted traitswith references in stored in


Fig 2.1: Biometric System [8]

Classification of biometric identification systems:

Biometrics systems is broadly classified into two types

‘ Physical biometrics: It is based on data derived

from direct measurements of parts of the human

body. Fingerprints, iris, retina, hand geometry and

facial recognition are some of the leading

physiological biometrics.

‘ Behavioral characteristics: Identification of the

person is based on his unique behavioral

characteristics. These characteristics can be voice,

speech, signature, and rhythm of typing or an

individual’s walking style (gait). Even though the

behavioral biometrics is dependent on the actions

of an individual, it is also influenced by the

physical structure of the human body.


Following section lists the various Behavioral Biometrics


‘ Keystroke or Typing Recognition:

‘ Speaker or Voice Authentication:

A voice biometric is a numerical representation of

the sound, rhythm, and also pattern of an

individual’s voice. A voice biometric or “voice

print,” is as unique to an individual as any other

biometric methods. Voice authentication is a fairly

simple process. To register, a user records the

sample of his voice and it is stored in the

authenticating system as ‘voiceprint’. If the user

wishes to access the resource, a sample of their

voice is given to the system. A comparison is made

between the input and voiceprint to validate that

the right person is given the access to the resource.

Following section lists the various Physical Biometrics


‘ Fingerprint Identification or Recognition:

Fingerprint technology is also known as

dactyloscopy. It is a technique of identification

where comparison is made between two instances

of fingerprints to determine whether they are from

same sources. This technique requires to compare

several features of fingerprints that are found

unique for an individual. The ridges and minutia

points are unique for an individual. The ridges can

be of three types: loop, whirl and arch .Minutia

points are specific points on fingerprints which are

critical for identification. These features of fingers

are captured as an image with help of scanner and

is enhanced and converted to a template. The

template is an encrypted biometric key or

mathematical information. The image of the

fingerprint is not stored. The algorithm cannot

convert this template back to image. Hence it is

difficult to replicate fingerprints. Scientists have

discovered that the fingerprints are inherited. It is

possible to have a belief that the members of a

family share the same fingerprint pattern

‘ Hand or Finger Geometry Recognition:

Hand geometry identifies an individual based on

the unique features of the hand. The unique

features may be length of finger, its thickness, the

distance between the finger joints and overall

structure of the bone. The system consists of a

camera which captures the image of the hand. The

necessary features are extracted, processed and

stored in the database. These stored templates can

be used later for the purpose of verification.

‘ Facial Recognition:

Face Recognition systems have the ability to

identify an individual based on the various features

on the face. Human face has several distinguishable

features called the nodal points. There are about 80

different nodal points on the face. Some of which

are the width of the nose, distance between eyes,

length of the jawline, shape of the face based on

cheek bones,depyh of the eye sockets and many

more.The positions of these nodal points are

calculated using appropriate algorithms like PCA

and LDA.The emerging trend in face recognition is

3D face recognition systems which have better

levels of accuracy when compared to the older




Drawbacks of various biometric systems are given below:

‘ Fingerprint:


Volume: 03 Issue: 01 | Jan-2014, Available @ 2

IJRET: International Journal of Research in Engineering and TechnologyeISSN: 2319-1163 | pISSN: 2321-7308

‘ Injuries, traumas, wounds or cuts can make the

fingerprint reading unidentifiable.

‘ Distortions due to grease, dirt or contamination on

finger tips have the chances of the identification to

be rejected.

‘ Today’s scanners are still not able to differentiate

between real and fake fingerprints. Fake

fingerprints can be tricked using gelatinized molds

over real finger

‘ Facial recognition:

‘ Pose variations, ageing are still the limiting factors

to identify the person using face recognition.

‘ Use of 2D scanners can’t handle pose variations

and are sensitive to variations in light and shadows.

‘ The use of 3D scanners eliminates these limits but

are expensive and have time constraints.

‘ Voice recognition:

‘ These systems are susceptible to error in the

presence of noise and external sounds. The distance

of the microphone from the user also affects the

accuracy rates.

‘ Prerecorded voice can be used for malicious


‘ These systems take time to adjust to the voice of an

individual and require large amount of memory to

store voice files.

‘ Iris and retinal recognition:

‘ The distance of the person from the camera affects

the performance of the system.

‘ Errors might occur due to reflection caused by

spectacles, eyelashes or lenses.

‘ During the scanning process the person is required

to remain still.

‘ The equipment used are expensive.

‘ Hand geometry based recognition:

‘ Complications might arise when used with certain

populations. There can be a perception of bio-

hazard due to spread of potential germs.

‘ Possible changes to the shape of hands s can cause

failure of the system.

‘ Signature

‘ These kinds of systems have the limitation factor of

inconsistent signature. A person without a constant

signature may not be recognized or an individual

with muscular illness may face difficulties in

proving their identification.

‘ The quality of ink and paper may also account for


‘ Keystroke

‘ The major drawback is low accuracy rates due to

the varying rhythms of typing. These variations

may be due to injury, fatigue, distractions, and

mood or due to the side effects of drugs,

medications or consumption of alcohol.

‘ DNA recognition:

‘ As it is a very new technology, may not be very

accurate among close relatives and hence less

popular in public.

‘ Requires time to process and establish identity.

‘ Requires expensive equipment for processing and

analyzing the samples.



ECG based biometric is a recent topic for research. The

ECG record is a graphical record of electrical impulses of

heart. Electrical activity of the heart is represented by ECG

signal. Capturing the ECG signal without the cooperation

from the person is a difficult task. Hence cannot be copied

easily to provide fake identity. One of the most important

strengths of ECG is that it accounts for the vitality of a

person. Hence it requires that the person has to be

necessarily present at the time of authentication.

All these factors assure better security when compared to

other biometric traits which were discussed earlier. Hence

ECG can become the most promising biometrics in the near


Description of ECG waveforms: The ECG is characterized

by five different segments of the waveform: the P, Q, R, S

and T Waves. [9] The analysis of each of the segments gives

information about the different events of the Cardiac cycle

as in fig 5.1:

P-wave: It is a small low-voltage deflection caused due to

the atrial depolarization.

QRS complex: The largest-amplitude portion of ECG,

caused due to the currents generated due to the ventricular

depolarization.It is made of thre closely related waves Q-

wave,R-wave and S wave.

T-wave: It represents ventricular repolarization.

P-Q interval:It is the time interval between the beginning of

the P wave and the beginning of the QRS complex.


Volume: 03 Issue: 01 | Jan-2014, Available @ 3

IJRET: International Journal of Research in Engineering and TechnologyeISSN: 2319-1163 | pISSN: 2321-7308

Features that make ECG unique

ECG is unique as the morphology and the amplitudes of the

cardiac cycle are dependent on the size, shape and position

of the heart. The most variable factor of heart is the

heartbeat. The normal heart beat of a person is around 60-80

beats/min. This may rise to 200beats/min under pressure or

excitement. This variation may reduce the diastole duration

and ventricular depolarization. It may also cause the

attenuation of the R wave amplitude. But the duration of

QRS complex does not vary significantly.

Generally the raw ECG signal is contaminated by noise and

hence requires preprocessing to remove the disturbances.

Once preprocessing is done, Feature has to be extracted for

the purpose of authentication. The features that can be

extracted are:

Angle features: The angle between PQR, QRS and RST in

the ECG signal can be used.

Interval features: The time interval between two R peaks can

also be used as one of the features. The others are the time

difference between a peak and a valley or between two

peaks or two valleys.

Amplitude features: The difference between the amplitudes

of two peaks or two valleys or one peak and a valley can be

the features extracted for authentication.

The feature to be extracted has to be selected carefully based

on feasibility, consistency and accuracy rates. The angle and

interval features are not constant .This because of the fact of

the heart beat rate changes from a child to an adult. Hence

these features are not suitable. But the amplitude features do

not change with age and remain almost constant. Hence the

amplitude features may be more suitable for the purpose of




We have listed following areas where we can have an

authentication process via. ECG.

‘ In attendance management systems usually ID

‘ In e-voting machines, ECG can be used as key

‘ In locking systems present in mobile phones,

‘ It can be used in the field of telemedicine to

‘ Used in application involving financial

‘ Used as digital signature to file income tax

‘ May be used in Aadhar cards. Aadhar is 12

‘ Can be used as factor of identification of a

‘ Gain access control over data files and

cards are used for validating the presence of an

individual. It is possible for a person to forget

his ID at home but very unlikely to forget his

heart at home. It is also difficult to make proxy

attendance using ECG.

factor of single vote. A person can cast single

vote. Addition of fake votes or multiple votes

can easily be identified and rejected.

house doors, bank lockers, vehicles etc.

monitor a patient’s health over long distances

using ECG as identifying factor.

transactions like net banking, ATM systems,

online shopping systems etc.

returns, eProcurement, eTendering, sending

and receiving encrypted mails etc.

digits unique ID issued to every citizen of

India. This single source of truth will help in

financial inclusions, with deeper penetration of

financial institutions and smooth error free

distributions of governmental schemes. It card

has fingerprints and irises captured. It is likely

to fake these biometric factors. But if ECG

based identification is used it is difficult to

clone the uniqueness of a person.

person in international border crossing and

henceforth avoid the illegal trespassing,

smuggling activities and other anti-social


computer programs which contain personal

and crucial information which is of importance

to the military, investigations bureaus,

revenue, defense and other government

organizations. It is very important to maintain

secrecy for these agencies.

fig 5.1


This paper has evaluated the purpose of using ECG

enabled biometric authentication system. Unlike

conventional biometrics that is neither secure nor

robust enough against falsification, ECG is

inherited to an individual is highly secure and

impossible to be forged. The most important

feature of ECG is its real-time feature of vitality.

This ensures that ECG cannot be acquired from a


Volume: 03 Issue: 01 | Jan-2014, Available @ 4

IJRET: International Journal of Research in Engineering and TechnologyeISSN: 2319-1163 | pISSN: 2321-7308

dead person and compulsorily requires the presence

of the person at the time of authentication. ECG is

the most promising biometric feature due to its

uniqueness, universality and acceptability. The

characteristic of permanence is also a key factor for

it to emerge as an excellent biometric system in the

near future


[1] [Drawbacks Of Various Approaches] Found at,


[2] [Drawbacks Of Various Approaches] Found at,


[3] ] B Rodger Jamieson, Ph.D., CA, Greg Stephens and

Santhosh Kumar ‘Fingerprint Identification: An Aid to the

Authentication Process’, Information Systems Audit and

Control Association.

[4]NicosMaglaveras, TelemachosStamkopoulos,

KonstantinosDiamantaras, Costas Pappas, Michael Strintzis

‘ECG pattern recognition and classi??cation using non-

linear transformations and neural networks: A review’,

International Journal of Medical Informatics 52 (1998) 191-


[5]Fahim Sufi, Ibrahim Khalil, and Jiankun Hu, ‘ECG-

Based Authentication’, Chapter 17, Handbook of

Information and Communication Security (Eds.)

[6][Biometric authentication] found at,


[7]Abhishek Kumar Sinha, ‘Financial Transactions get

personalized and secure with biometrics’, Digital



‘Identification of Individuals using Electrocardiogram’,

IJCSNS International Journal of Computer Science and

Network Security, VOL.10 No.12, December 2010

[9]Dr.Neil Townsend, ‘Medical Electronics’,Michaelmas

Term 2001 found at pno 7

[10]Steven A. Israel, John M. Irvine, Andrew Cheng,

MarkD.Wiederhold,Brenda K. Wiederhold ‘ECGto identify

individuals’,PatternRecognition,The journal of pattern

recognition society.


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