Introduction to CBIRF and Biometrics

Frank Yeong-Sung Lin

Department of Information ManagementNational Taiwan University

EMBA 2009 – Information Systems and ApplicationsLecture III

Outline

Introduction to CBIRFIntroduction to (face-based) biometricsDiscussions

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Introduction to CBIRFCBIRF – Content Based Image/Information Retrieval and Filtering Characteristics

Adoption of only color, texture, shape and object position/size/orientation information in an imageNo metadata or human indexing/annotation requiredReal-time responseHigh scalabilityHigh availability/reliabilityInternet as the search targetRelevance feedback (learning)

Other applicationsAnti-pornography EngineAnti-leakage Engine (for protection of confidential images)

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Introduction to CBIRF (cont’d)

Content based image retrieval

Characteristics Feature extraction High dimensional indexing Relevance feedback (learning)

Image Features (color, texture, shape…)

Database

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Introduction to CBIRF (cont’d)

Query/Seed Image

Search Results

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Applications of CBIRF

Image searchVideo searchLogo searchIPR protectionConfidential image managementObjectionable image managementImage and photo organizerBiometrics

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Extension of CBIRF— Porn Filtering

Anti pornography engine

Applications1. Email filtering2. Desktop content management3. Porn blacklist collection4. Objectionable URL/Web content

blocking

Pornography Pornographic Features Database

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Extension of CBIRF— Leakage DetectionAnti (confidentiality/privacy) leakage engine

Applications1. Email filtering2. Confidential content management

Confidential Images

Features

Database

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Introduction to Biometrics

Total biometrics industry revenue would grow from more than US$3.4 billion in 2009 to more than US$9.3 billion in 2014 (excluding the revenue from related professional and integration services).

(International Biometric Group, 2009-2014)

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Introduction to Biometrics (cont’d)

TLJ Confidential

• Remarks by Bill Gates, Chairman and Chief Software Architect, Microsoft CorporationIT Forum 2004Copenhagen, Denmark, November 16, 2004

• Passwords will soon be a thing of the past, replaced by biometric and smart-card technology, Bill Gates reiterated on Tuesday. – from Tech News on ZDNews

• Another major issue for identity systems is, of course, the weakness of the password. Passwords have been the primary way that people identify who they are. Unfortunately, for the type of critical information on these systems and the regulations that ask that these systems be secure, whether it is health data, financial data or customer access to customer records where only certain people should have that information, we are not going to be able to simply rely on passwords. Therefore, moving to biometric identification and particularly in moving to smart cards, is a way that is coming. This is something that has been talked about for several years, but now we finally see the leading edge customers taking that step.

• From “(i) what you have” to “(ii) what you know about” and eventually to “ (iii) who you really are”

• ICAO advocates biometrics technologies, particularly face-based, for passport holder authentication.

Introduction to Biometrics (cont’d)

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Introduction to Biometrics (cont’d)

First choice

Biometric Types Defined by ICAO (International Civil Aviation Organization)

Introduction to Biometrics (cont’d)

The Enrollment Process

Photo Taking Facial Area PositioningFace Detection

Facial Feature Extraction from the Facial Area

Facial Feature Archiving into the Specified Storage Device as a “Gallery”

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Introduction to Biometrics (cont’d)

The Facial Feature Verification Process

Photo Taking Facial Area PositioningFace Detection

Facial Feature Extraction from the Facial Area

Retrieval of the Enrolled Facial Feature (Gallery) from the Storage Device

Intelligent Comparison of the 2 Feature Sets Comparison Result Reporting

ACCEPT

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Introduction to Biometrics (cont’d)

Advantages of face-based over fingerprint-based biometric approaches

More convenientLess intrusiveMore hygienicLeveraging on existing infrastructure (webcam)Less prone to duplicate (fingerprints easily available on protected devices, e.g. NBs)Capable of continuous verificationVerifiability by human eyes Effects of deterrence and non-repudiation by logging probe/novel images

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Introduction to Biometrics (cont’d)

Characteristics of desirable face verification technologies

• Suitability for PCs/NBs/UMPCs/PDAs/Mobile Phones• Insensitivity to lighting, pose, expression and accessory variations• Low enrollment time• Low verification time• User adjustable and personalized sensitivity• Dynamic thresholding• Intelligent and self-learning galleries• Factuality/Liveness detection• Extremely high accuracy: e.g. product of FAR (False Acceptance Rate) & FRR (False Rejection Rate) lower than 10-6

• Integration with other, e.g., the credential (ID and password) mechanism 16

Merry Christmas and Happy New Year!

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