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Biometrics

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06/26/2022 1 By 07BCE095 DIVYA SHAH BIOMETRIC AUTHENTICATION
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Page 1: Biometrics

04/08/2023 1

By 07BCE095DIVYA SHAH

BIOMETRIC AUTHENTICATION

Page 2: Biometrics

04/08/2023 2

Contents – biometric systems

1. Biometric identifiers2. Classification of biometrics methods3. Bio Introduction4. metric system architecture5. Performance evaluation6. Signature recognition7. Voice recognition8. Retinal scan9. Iris scan10. Face-scan and facial thermo gram11. Hand geometry

Page 3: Biometrics

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Personal identification objects

Token-based: “something that you have”

Knowledge-based: “something that you know”

Biometrics-based: “something that you are”

Page 4: Biometrics

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Definition of Biometrics

Any automatically measurable, robust and distinctive physical characteristic or personal

trait that can be used to identify an individual or verify the claimed identity

of an individual.

Biometrics is the automatic recognition of

a person using distinguishing traits

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Some applications

Financial security Physical access control, Benefits distribution, Customs and immigration, National ID systems, Voter and driver registration, Telecommunications

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Biometric identifiers

Universality Uniqueness Stability Collectability Performance Acceptability Forge resistance

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Classification of biometrics methods

Static

fingerprint retinal scan iris scan hand

geometry

Dynamic

signature recognition

speaker recognition

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Biometric system architecture

Basic modules of a biometric system

Data acquisition Feature extraction Matching Decision Storage

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Biometric system model

Raw data Extracted f eatures

template

Authentication decision

Data collection Signal

processing

matching storage

score

decision Application

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Data acquisition module

Reads the biometric info from the user.

Examples: video camera, fingerprint scanner/sensor, microphone, etc.

All sensors in a given system must be similar to ensure recognition at any location.

Environmental conditions may affect their performance.

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Feature extraction module

Discriminating features extracted from the raw biometric data.

Raw data transformed into small set of bytes – storage and matching.

Various ways of extracting the features.

Pre-processing of raw data usually necessary.

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Matching module

The core of the biometric system.

Measures the similarity of the claimant’s sample with a reference template.

Typical methods: distance metrics, probabilistic measures, neural networks, etc.

The result: a number known as match score.

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Storage module Maintains the templates for enrolled

users.

One or more templates for each user.

The templates may be stored in: a special component in the biometric

device, conventional computer database, portable memories such as smartcards.

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Possible decision outcomes

A genuine individual is accepted.

A genuine individual is rejected (error).

An impostor is rejected.

An impostor is accepted (error).

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Biometric technologies

Signature recognition Voice recognition Retinal scan Iris scan Face biometrics Hand geometry

Page 16: Biometrics

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Signature recognition

Variety of characteristics can be used

› angle of the pen› pressure of the pen› total signing time› velocity and acceleration› geometry

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Fingerprint recognition

Ridge patterns on fingers uniquely identify people.

Classification scheme devised in 1890s.

Major features: arch, loop, whorl.

Each fingerprint has at least one of the major features and many ‘small’ features.

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Eye biometric

Retina Back inside of the eye ball.

Pattern of blood vessels used for identification.

Iris colored portion of the eye surrounding the pupil.

complex iris pattern used for identification.

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Speaker recognition

Linguistic and speaker dependent acoustic patterns.

Speaker’s patterns reflect: anatomy (size and shape of mouth and

throat), behavioral (voice pitch, speaking style).

Heavy signal processing involved (spectral analysis, periodicity, etc)

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Face-scan and Facial Thermograms

Static controlled or dynamic uncontrolled shots.

Visible spectrum or infrared (thermo grams).

Non-invasive, hands-free, and widely accepted.

Questionable discriminatory capability.

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Hand geometry

Features: Dimensions and shape of

the hand, fingers, and knuckles as well as their relative locations.

Two images taken: One from the top and

one from the side.

Page 22: Biometrics

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Thank you


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