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Introduction to Biometrics

Introduction to Biometrics. Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #6 Guest Lecture + Some Topics in Biometrics September 12, 2005. Outline. Guest Lecture Some Topics in Biometrics. Introduction to Biometrics. Guest Lecture

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Introduction to Biometrics

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  1. Introduction to Biometrics Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #6 Guest Lecture + Some Topics in Biometrics September 12, 2005

  2. Outline • Guest Lecture • Some Topics in Biometrics

  3. Introduction to Biometrics Guest Lecture Image Feature Extraction and Annotation September 12, 2005

  4. Some Topics in Biometrics • Reference • http://biometrics.cse.msu.edu/info.html • Papers published on the web by researchers at Michigan State University • Overview • Fingerprint Identification • Hand Geometry • Face Location • Multi-Biometrics

  5. Overview • Biometrics is the automatic identification of a person based on his/her physiological and behavioral characteristics • Verification vs. Identification • Am I whom I claim I am? • Who am I? • Applications • Criminal identification, ATMs, Cellular Phones, Smart cards, PCs, E-Commerce, Automobiles (biometrics replacing car keys)

  6. Fingerprint Identification • Finger-print matching • Two categories: Minutiae based, Correlation based • Minutiae-based techniques • First find the minutiae points and then map their relative placement on the finger • Issues: difficult to extract minutiae points if fingerprinting is of low quality • Correlation-based techniques • Spatial correlation of regions • Issues: Affected by Image translation

  7. Fingerprint Identification (Concluded)) • Finger-print classification • Classify the fingerprints so that search time is reduced • Form groups of fingerprints; Classification is obtained by matching with pre-specified types of finger-prints • When a new finger-print arrives try and place it into a group • Classification based data mining/machine learning algorithms such as K-Nearest Neighbor • Fingerprint Image Enhancement • Algorithms to enhance the finger-print • This is expected to facilitate finger-print matching • Makes it less difficult to extract minutiae from fingerprints

  8. Hand Geometry • Uses geometric shape of hand for authenticating user’s identity • Combine various individual features of hand for effective verification • Human hand is not in general unique (not the case with fingerprints) • Reason one may want to use hands instead of finger-prints is to ensure privacy • Some pros and cons • Hand geometry gives better privacy • But hand geometry is not unique; therefore may be used for verification • Not suitable for identification

  9. Face Location and Retrieval • Problem • Given an arbitrary black and white still image, find the location and size of every human face it contains • Applications • First step in automatic face recognition • Image database indexing • Search by content for surveillance systems

  10. Multi-Biometrics • Integrating Faces and Fingerprints for Identification • Single biometric may not be effective • Integrate multiple biometrics such as fingerprints and faces • Fingerprint, Face and Speech • Better to use a third biometric and that is speech • Challenge • What is an effective combination of biometrics?

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