EMBA 2009 – Information Systems and Applications Lecture III

1. Introduction to CBIRF and BiometricsFrank Yeong-Sung LinDepartment of Information ManagementNational Taiwan University EMBA 2009 – Information Systems and Applications Lecture III

2. Outline • Introduction to CBIRF • Introduction to (face-based) biometrics • Discussions 2

3. Introduction to CBIRF • CBIRF – Content Based Image/Information Retrieval and Filtering • Characteristics • Adoption of only color, texture, shape and object position/size/orientation information in an image • No metadata or human indexing/annotation required • Real-time response • High scalability • High availability/reliability • Internet as the search target • Relevance feedback (learning) • Other applications • Anti-pornography Engine • Anti-leakage Engine (for protection of confidential images) 3

4. Introduction to CBIRF (cont’d) Content based image retrieval Characteristics Feature extraction High dimensional indexing Relevance feedback (learning) Image Features (color, texture, shape…) Database 4

5. Introduction to CBIRF (cont’d) Search Results Query/Seed Image 5

6. Applications of CBIRF Image search Video search Logo search IPR protection Confidential image management Objectionable image management Image and photo organizer Biometrics 6

7. Extension of CBIRF— Porn Filtering Anti pornography engine Applications Email filtering Desktop content management Porn blacklist collection Objectionable URL/Web content blocking Pornography Pornographic Features Database 7

8. Extension of CBIRF— Leakage Detection Anti (confidentiality/privacy) leakage engine Applications Email filtering Confidential content management Features Database Confidential Images 8

9. 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) 9

10. Introduction to Biometrics (cont’d) TLJ Confidential 10

11. Introduction to Biometrics (cont’d) • 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. 11

12. Introduction to Biometrics (cont’d) Biometric Types Defined by ICAO (International Civil Aviation Organization) First choice 12

13. Photo Taking Face Detection Facial Area Positioning Facial Feature Extraction from the Facial Area Facial Feature Archiving into the Specified Storage Device as a “Gallery” Introduction to Biometrics (cont’d) The Enrollment Process 13

14. Photo Taking Face Detection Facial Area Positioning Facial Feature Extraction from the Facial Area Retrieval of the Enrolled Facial Feature (Gallery) from the Storage Device ACCEPT Intelligent Comparison of the 2 Feature Sets Comparison Result Reporting Introduction to Biometrics (cont’d) The Facial Feature Verification Process 14

15. Introduction to Biometrics (cont’d) • Advantages of face-based over fingerprint-based biometric approaches • More convenient • Less intrusive • More hygienic • Leveraging on existing infrastructure (webcam) • Less prone to duplicate (fingerprints easily available on protected devices, e.g. NBs) • Capable of continuous verification • Verifiability by human eyes • Effects of deterrence and non-repudiation by logging probe/novel images 15

16. 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

17. Merry Christmas and Happy New Year! 17