biometric feasibility analysis3

8/14/2019 Biometric Feasibility Analysis3

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Feasibility

Analysis (I)Final Year Project Part

1PRESENTED BY : DAYANI A/P MURALI

: 1031125472

: B.Eng. (Hons) Electronicsmajoring in Bio-Instrumentation

SUPERVISOR : MS.HIDAYATI ABDUL AZIZ

MODERATOR : MR.KHAIR RAZLAN OTHMAN


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OBJECTIVES To study various types of

biometric identification

method

To do experiment and analysis

on the strength and weaknessofphysiological signalbiometric compared to physical

biometric method


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OVERVIEW OF PROJECT

Biometric

Biometric method

Project aim


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PART 1


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OUTLINE OF

PRESENTATION Introduction on biometrics Types of biometric identification

Characteristics of biometrics Biometric system Feature Selection Feature Extraction Implementation on Part 1- Fingerprint Conclusion on Part 1 Implementation on Part 2- ECG


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INTRODUCTION TO

BIOMETRICS a way of analyzing problem in biological sciences. to recognize or identify the difference between two

individual.

Biometrics used

In two major ways

Identification

(determining who

a person is)

Verification/

Authentication

(determining if

a person is who

they say they are)


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3 Basic

types of

classification

Physical Behavioral Physiological

FingerprintIrisHand Geometry

FaceVein Patterns

SignatureVoiceKey stroke

ECGEEG


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Physical Characteristics Physical biometrics

measures the inherentphysical characteristics onan individual.

It can be used for either

identification or verification.


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FINGERPRINT VEIN PATTERN

BERTILLONAGE


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HAND GEOMETRY FACE

IRIS


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Physiological

-measures thecharacteristics acquiredfrom the internal body

condition.


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Electrocardiogram


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Electroencephalogram

(EEG)

A

B


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Behavioral CharacteristicsBehavioral biometrics basically measures thecharacteristics which are acquired naturallyover a time. It is generally used for

verification SIGNATURE

VOICE

KEYSTROKE


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Characteristics of

Biometrics Unique

Measurable

Universality

Permanence

Performance Acceptability

Circumvention


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eps on app ca on oBiometrics

ENROLLMENTDATA

STORAGE

COMPARISON

/MATCHING

TRANSMISSION

SIGNAL

PROCESSING

MATCHING

ALGORITHMSENSOR

DATA STORAGE

Biometrics System


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FEATURE SELECTIONFEATURE SELECTION Selecting a subset of relevant features for

building robust learning models.

A process done before feature extraction

FEATURE EXTRACTIONFEATURE EXTRACTION Process of developing a representation for or a

transformation from the original data

Also a special form of dimensionality reduction. Process of transforming/ filtering/ reducing the

input data


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FEATURES

GENERAL FEATURES

COLORTEXTURESHAPE

DOMAIN-SPECIFIC

FEATURES

FACEFINGERPRINT


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Methods of FeatureExtraction

Pre-processing This is an imageenhancement process.

Feature extraction extractionof the unique feature

Post processing Removal offalse details


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IMPLEMENTATION OF PART1


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Basics of fingerprints

1

2


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LEFT LOOP RIGHT LOOP DOUBLE LOOP

TENTED ARCHARCHWHORL


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Preprocessing stage

(image

enhancement)

Enhance color

Brightness,

Contrast

Remove noise


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Binarization and

skeletoning

enhanced image is binarised.

skeleton of image is obtained.

- To obtain ridge which is one pixelwide

A minutiae is extracted.

- Minutiae point is either the ridgeending or ridge bifurcation of the onepixel ridge


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Post processing

The features obtained after

extraction may contain falsedetails.


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Types of false details

Spike

Hole

Spur Ladder

Break

Bridge


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3 levels of involved in thefiltering of false minutiae:

Level 1: Removes the false ridgeending.

Level 2: Removes the first five typesof minutiae .

Level 3:limiting the maximumnumber of minutiae present in thethinned image


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Experimental Results onImage Enhancement

1 2 3


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Experimental Resultson Feature Extraction

4 5 6


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8877


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CONLUSION (PART 1)

By studying the various typesof biometric identification

method, we are able to identifythe strength and weaknessesof the specified method in the

second part of the final yearproject and thus, will be ableto produce a more reliableresult at the end of the

ro ect.


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Implementation for FYPPart 2


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THANK YOU

biometric feasibility analysis3

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