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SEMINAR BY

M.RUPALY REDDY

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     Complex and largely software basedtechnique

     Analyze unique shape, pattern & positioning of facial features

     

It compare scans to records stored incentral or local database or even on asmart card

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     It is a unique measurable characteristics of a

human being.

     Used to automatically recognize an individual¶s

identity     Two types 1.physiological &

2. behavioral characteristics

      A ³biometric system´ refers to integrated

hardware and software used to conduct

biometric identification

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` Two types of comparison in face recognition

1.Verification- The system compare the given

individual with who that individual says they are.

2 .Identification-The system compares a given

individual to all the other individuals in the database

and gives a ranked list of matches.

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Capture Extraction Comparison

Match/Non

match

 Accept/Reject

STAGES OF IDENTIFICATION

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` Capture-Capture the biometric sample

` Extraction-unique data is extracted from the

sample and a template is created.

` Comparison-the template is compared with a new

sample.

` Match/non match-the system decides whether the

new samples are matched or not.

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` Enrollment module-An automated mechanism that

scans and captures a digital or analog image of a

living personal characteristics

` Database-Another entity which handles compression

,processing ,data storage and compression of the

captured data with stored data

` Identification module-The third interfaces with the

application system

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FaceSystem

Data base

Preprocessing&

segmentation

Analysis AnalysisData

Preprocessing&

SegmentationAnalysis

Face rag &

scoring

Enrollment Module

reject

Verification Module

User Interface

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` False Acceptance Rate [FAR]

` False Rejection Rates [FRR]

` Response time

` Threshold/decision Threshold

` Enrollment time

` Equal error rate

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` Data acquisition

` Input processing

` Face image classification

` Decision making

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` Detection

`  Alignment

` Normalization

` Representation

` Matching

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` Convenience and social acceptability

` Easy to use

` Inexpensive biometric

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` Face recognition systems can¶t tell the difference

between identical twins

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     Government Use

1. Law enforcement

2.Security/counterterrorism

3.Immigration      Commercial Use

1.Day care

2.Residential security

3.Voter verification4.Banking using ATM

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Face recognition technologies have been

associated generally with very costly top secure

applications. Today the core technologies have

evolved and the cost of equipments is going down

dramatically due to the integration and the

increasing processing power. Certain applications

of face recognition technology are now cost

effective ,reliable and highly accurate. As a result

there are no technological or financial barriers for stepping from the pilot project to widespread

deployment

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