MULTIMODAL BIOMETRICS SYSTEM

PRESENTED BYII MCA ‘A’PSNACET.

A biometric system is a technological system that uses information about a person (or other biological organism) to identify that person.

In computer security, biometrics refers to authentication techniques that rely on measurable physical characteristics that can be automatically checked.

BIOMETRICS

Traditional methods involving passwords and PIN numbers

Biometrics highest level of security

Why we use biometric??

There are several types of biometric identification schemes:

face : the analysis of facial characteristics

fingerprint : the analysis of an individual's unique fingerprints

hand geometry : the analysis of the shape of the hand and the length of the fingers

retina : the analysis of the capillary vessels located at the back of the eye

iris : the analysis of the colored ring that surrounds the eye's pupil

signature : the analysis of the way a person signs his name.

vein : the analysis of pattern of veins in the back if the hand and the wrist

voice : the analysis of the tone, pitch, cadence and frequency of a person's voice.

TYPES OF BIOMETRICS

Accurate Identification

Accountability

Easy and Safe for Use

Time Saving

User Friendly Systems

Security

Versatility

Scalability

Return on Investment

Advantage of biometric

multimodal unimodal

• Multimodal biometrics refers to the use of a combination of two or more biometric modalities in a verification / identification system.

• Identification based on multiple biometrics represents an emerging trend

• Unimodal biometrics refers to the use only one biometrics for verification/identification.

Susceptibility of biometric sensors to noise. This can lead to inaccurate matching, as noisy data may lead to a false rejection.

Noise in sensed data,due to imperfect acquisition conditions,the captured biometrics traits might be noisy or distorted.

It is not affect the spoofing It is vulnerable to Spoofing the data

Multimodal vs unimodal

Data Collection

Transmission

Signal Processing

Data Storage

Decision

Biometric system

biometric

How to work it??

System architecture USM

LSIIT, CNRS-ULP, Groupe de Recherche en Intelligence Artificielle

Pour plus de renseignements : Pr J. Korczak, Mr N. Poh <jjk, poh>@dpt-info.u-strasbg.fr

IdentitéAccepter,Rejeter

w1

w2

Effacer les silences

Transformation de l’ondelette

C0 C1 C2 C3 C4 C5 C6 C7

C9 C10 C11 C12

C13 C14

C15

Fré

quen

ce

Temps

Normalisation + Codage

Réseau des neurones

Apprentissage et Reconnaissance

Détection des yeux

Average Intensity of each row s

-50

0

50

100

150

200

250

0 10 20 30 40

Grey Scale

Intensity

-50

0

50

100

150

200

250

0 10 20 30 40 50

Intensity

Trouver X

Trouver Y

Filtre de base

Inondation +Convolution

Extraction

Normalisation + Codage

MomentVert

Bleu

Hue

Saturation

Intensité Réseau des neurones

Apprentissage et ReconnaissanceVisage

Voix

Base des données

Décision

REFERENCES

[1] K. Jain, A. Ross, S. Prabhakar,“An introduction to biometric

recognition”, IEEE Transactions on Circuits and Systems for

Video Technology, Vol. 14, pp. 4–20, 2004.

[2] D. Zang,“Automated Biometrics: Technologies and Systems”,

Kluwer Academic Publishers, USA, 2000.

[3] Chander Kant, RajenderNath,“Reducing Process-Time for

Finger print Identification System”, International Journals

of Biometric and Bioinformatics, Vol. 3, Issue 1, pp.1- 9,

2009.

[4] A.K. Jain, A. Ross,“Multibiometric systems”, Communication

Comparison

Comparison of biometric methods

Criminal identification

Prison security

ATM

Border crossing controls

Database access

application

CONCLUSION

A good biometric recognization system is characterized by use of a feature that is uniqueness.

That mean any two people have same characterstics will minimal . The biometric system have two type of recongization one is positive recognization and another one is negative recognization. It main purpose is verification process.

3/24/15