face recognition tech

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WELCOME WELCOME



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FACE FACE

RECOGNITION RECOGNITION

TECHNOLOGY TECHNOLOGY

VISHNU V S7 ECE B

MCET



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FACE RECOGNITIONFACE RECOGNITION

BIOMETRICS

EVOLVING APPROACHES TO RECOGNIZING

FACES: ± EIGENFACE TECHNOLOGY

± LOCAL FEATURE ANALYSIS

± NEURAL NETWORK TECHNOLOGY

ADVANTAGES/DISADVANTAGES FUTURE



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FACE RECOGNITION:FACE RECOGNITION:What is it ?What is it ?



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BIOMETRICS

BIOMETRICS

Biometrics - digital analysis using cameras or

scanners of biological characteristics such as facial

structure, fingerprints and iris patterns to matchprofiles to databases of people



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WHY DO WE NEED IT ?WHY DO WE NEED IT ? Quick way to discover cr iminals

Cr iminals can easily change their appearance

Fak e Id¶s Old ways are outdated



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EIGENFACE TECHNOLOGYEIGENFACE TECHNOLOGY



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EIGENFACE TECHNOLOGYEIGENFACE TECHNOLOGY BIOMETRIC SYSYEMS IN DEVELOPMENT FOR

OVER 20 YEARS

FACE IMAGE CAPTURED VIA CAMERA ANDPROCESSED USING AN ALGORITHM BASED ONPRINCIPLE COMPONENT ANALYSIS (PCA) WHICHTRANSLATES CHARACTERISTICS OF A FACE INTO

A UNIQUIE SET OF NUMBERS (TEMPLATE)

FACE PRESENTED IN A FRONTAL VIEW WITHWIDE EXPRESSION CHANGE



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A set of Eigenfaces -two-dimensional face-

like arrangements of light and dark areas, asshown to the right, ismade by combining allthe pictures and looking

at what is common togroups of individualsand where they differ most



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To identify a face, the program compares itsEigenface characteristics, which are encoded intonumbers called a template, with those in thedatabase, selecting the faces whose templates matchthe target most closely, as shown to the right



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LOCAL FEATURE ANALYSISLOCAL FEATURE ANALYSIS



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LOCAL FEATURE ANALYSISLOCAL FEATURE ANALYSIS Local feature analysis

considers individual

features. Thesefeatures are the building

blocks from which all

facial images can be

constructed.



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LOCAL FEATURE ANALYSISLOCAL FEATURE ANALYSIS Local feature analysis selects features in each face that differ

most from other faces such as, the nose, eyebrows, mouth

and the areas where the curvature of the bones changes.

Features



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To determine someone's identity,

(a) the computer takes an image of that person and

(b) determines the pattern of points that make that

individual differ most from other people. Then thesystem starts creating patterns,

(c) either randomly or

(d) based on the average Eigenface.




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(e) For each selection, the computer constructs aface image and compares it with the target faceto be identified.

(f) New patterns are created until

(g) A facial image that matches with the target canbe constructed. When a match is found, thecomputer looks in its database for a matchingpattern of a real person (h), as shown below.




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PERFORMANCE ISSUES

PERFORMANCE ISSUES

From Eigenface Technology to Local Feature Analysis,

the problems faced were same:

Images with complex backgrounds

Poor lighting conditions

Recognition accuracy.



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NEURAL NETWORKNEURAL NETWORK

TECHNOLOGYTECHNOLOGY



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Features from the entire

face are extracted as visual

contrast elements such asthe eyes, side of the nose,

mouth, eyebrows, cheek-

line and others (Feature

Extraction).

The features are quantified,

normalized and compressed

into a template code.

NEURAL NETWORKNEURAL NETWORK

TECHNOLOGYTECHNOLOGY



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ARTIFICIAL NEURAL NETWORK

Valid user/

Invalid

user?

2 f

3 f

4 f

5 f

6 f

1 f

7 f

Feature

Extraction

Features provided

to ANN

ANN technology gives com puter systems an amazing capacity to actually lear n from

in put data.

In put

Layer

Hidden

Layer Output

Layer



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Since,the neural network learns from experience, itdoes a better job of accommodating varying

lighting conditions and improves accuracy

over any other method.



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ADVANTAGES

DISADVANTAGES

Advantages

Less intr usive

Major secur ity boost

Fast

Sim ple Recognition

Disadvantages

Breach of pr ivacy

Com paratively less accurate

Expensive to im plement



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BIOMETRIC SYSTEMS INTEGRATION SERVICES

WHICH COMBINE FACE RECOGNITION SOFTWARE

WITH OTHER BIOMETRICS, SUCH AS IRIS, VOICE,SIGNITURE, FINGERPRINT AS WELL AS EXISTING

IDENTIFICATION CARD SYSTEMS

A PERSONS FACE WILL BE THE PRIVATE, SECURE

AND CONVENIENT PASSWORD

CONCLUSIONCONCLUSION



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BIB

ILIOGRAP

HYB

IB

ILIOGRAP

HY

1. ELECTRONICS FOR YOU- Part 1 Apr il 2001

Part2

May2001

2. ELECTRONIC WORLD - DECEMBER 2002

3. MODERN TELEVISION ENGINEERING- Gulati R.R

4. IEEE INTELLIGENT SYSTEMS - MAY/JUNE 2003

5. WWW.FACEREG.COM

6. WWW. IMAGESTECHNOLOGY.COM

7. WWW.IEEE.COM



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TH ANK YOU TH ANK YOU

face recognition tech

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