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Introduction to Biometrics

Introduction to Biometrics. Dr. Pushkin Kachroo. New Field. Face recognition from computer vision Speaker recognition from signal processing Finger prints from forensics and pattern recognition. Organization-1. Basics: Core biometric concepts General authentication protocols for

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Introduction to Biometrics

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  1. Introduction to Biometrics Dr. Pushkin Kachroo

  2. New Field • Face recognition from computer vision • Speaker recognition from signal processing • Finger prints from forensics and pattern recognition

  3. Organization-1 • Basics: • Core biometric concepts • General authentication protocols for • Verification • Identification • Screening • Most common • Finger, face, voice, iris, hand, signature, etc. • Skin reflectance, gait, etc.

  4. Organization-2 • Performance and Selection • Fundamental measurable aspects affecting system accuracy • Realistic Error Rates • System Issues • Overall design • Threat Models • Databases, APIs etc.

  5. Organization-3 • Mathematical Analyses • Analyses for Evaluation and Selection of Biometric System • Stochastic Methods • Optimzation (Error minimization)

  6. Authentication • Standard Methods: • ID cards, passports etc. • Problems: • Misplaced, get lost, forged • Automating identification

  7. Biometrics • Biometric Identification • Verification: (Easier) • Identification: (More difficult with large databases)

  8. Applications • Boarding an Aircraft • Performing a financial transaction • Picking up a child from daycare • Office and home security

  9. Distinct Personal Characteristics • Physiological • Static Measurement • Fingerprint, hand geometry etc. • Behavioral • Dynamic (temporal measurement) • Signature, gait, etc.

  10. Person Authentication • Three Traditional Modes • Possessions: keys, smart cards, passport etc. • Knowledge: Passwords, user ID, mother’s maiden name etc. • Biometrics: Physiological and Behavioral

  11. Two Authentication Methods • Verification: unique identifier which singles out a particular person (e.g. some I.D.) or person’s biometric. • Identification: Compare with an entire database.

  12. Desired Biometric Attributes • Universality: Each person should have it • Uniqueness: Each person different • Permanence: Invariant over time • Collectability: Sensors etc. • Acceptability: Legally, socially etc.

  13. Biometric Identifiers-1 • Common: • Physiological: • Face, fingerprint, hand geometry, Iris • Behavioral: • Signature • Voice

  14. Biometric Identifiers-2 • Used less (or emerging): • Physiological: • DNA, Ear Shape, Odor,Retina, Skin Reflectance, Thermogram • Behavioral: • Gait, keystroke, lip motion

  15. Biometric Subsystems • Biometric Readers (sensors) • Feature Extractors • Feature Matchers

  16. Authentication Systems • For Enrollment • For Authentication

  17. System Performance & Design Issues-1 • System Accuracy • False Accept Rate (FAR) • False Reject Rate (FRR) • Computation Speed • Scalability from small populations to large • Exception Handling: • Failure to use (FTU), Failure to Enroll (FTE), Failure to Acquire (FTA), etc.

  18. System Performance & Design Issues-2 • System Cost • Security • Privacy • Quantitative and qualitative parameters

  19. Biometric Identification • Reader, extractor, matcher (search in a database) • Positive Identification • Negative Identification

  20. Biometric Verification • Reader + I.D., extractor, Matching (with single) • Centralized databases • Distributed (e.g. smartcard stores the biometric features of the person)

  21. Biometric Enrollment • Positive Enrollment • Of people who match certain criteria for eligibility • Negative • For non-eligibility

  22. Biomeric System Security • System Analyses • Weakest point of failure • Point failure verses dynamic

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