biometric feasibility analysis3
TRANSCRIPT
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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