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Biometrics For Security Systems

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  • (e.g., face, fingerprint,iris, retina, hand geometry) (e.g., voice, gait)
  • Transcript

    • 1. Presented by SuhasDeshpande
      Dr. Druzgalski
      EE 507
      Advanced Topics in
      Biomedical Systems
      Fingerprint Identification Systems
    • 2. Overview
      Biometrics- different types
      Use of biometrics history
      Fingerprints
      Sensors
      Algorithms
      System on chip design
      Real life products
      US government Fingerprint programs
      FingerChip Project
      Companies
      References
    • 3. Biometrics
      “Biometrics refers to automatic identification of people based on their distinctive physiological and behavioral characteristics”
      “Biometrics is enabling technology that will make our society safer, reduce fraud and lead to user convenience”
      A typical biometric system is comprised of five components: A sensor, Signal processing algorithms,data storage component, A matching algorithm and a decision process.
      1,3
    • 4. History
      Babylonians (500B.C.) used clay tablets with fingerprints for business transactions
      Handprints used as signatures in drawings found inside caves about 31000 yrs old
      15thcentury:Chinesestarted using fingerprints to settle business transactions
      1892: Classification system for fingerprints (Galton)
      1896: Another classification system for fingerprints (Henry)
      1903: NY state prison uses fingerprint identification
      1963:A paper on Fingerprint automation published (Hughes)
      1969: FBI goes for the Automated Fingerprint recognition
      1975:FBI fund for minutiae ans sensor development for fingerprint identification
      1994: IAFIS held Fingerprint identification competition
      1999: FBI’s IAFIS components become operational
      1,2,3
    • 5. Fingerprints
      Finger skin is made of friction ridges which make different pattern in each individual
      There are main features like Arch, Loop and Whorl
      There are Minutiae like core,ridge ending, island, crossover, pore, bifurcation and delta
      Biomedical signal and image processing/Najarian
    • 6. Acquiring Fingerprints
      Rolled finger
      Static sensing
      Sweep reading
      (3)
    • 7. Sensors
      Optical sensors
      Capacitive sensors
      Electro optical readers
    • 8. Sensors
      Thermal sensors
      Tactile MEMS
      Ultrasound
      (7),(8)
    • 9. Fingerprint matching
      Minutiae based algorithms detect different Minutiae like delta, pores etc. It is difficult to detect and hence match the minutiae with poor quality of image
      Some algorithms use the shapes of the ridges after dividing the image in smaller cells. Ridge direction, phase and pitch are extracted
      (3)
    • 10. Fingerprint matching
      Correlation based algorithms follow the pattern o the ridges of the template to support or reject the fingerprint
      Some algorithms imply features such as ridge count and distance
      (3)
      http://biometrics.cse.msu.edu/fingerprint.html
    • 11. Problems !!!
      Poor quality images
      Some skin diseases like Psoriasis cause problems in fingerprint identification
      There are examples of people having no fingerprints
      Livelihood or enforcement has to be checked
    • 12. System on Chip
      With increase in number of application need for automation integrating the sensor and the algorithms
      The silicon chip is designed with the microprocessor, on chip memory and software algorithms
      (6)
    • 13. FingerChip Project
      The project started by Dr. Mainguet(Thomson) in 1995
      The Fingerchip sensor was rod shaped instead of shape of finger
      It used the sweep sensing technology
      It induced many aplications such as Laptops, USB drives, smart cards,
      (3)
    • 14. US government Programs
      US-VISIT's biometric procedures
      NIST Special Publication 800-76
      Integrated Automatic Fingerprint Identification System (IAFIS)
      Fast Capture of Rolled-Equivalent Fingerprints and Palm Prints
      1,3
    • 15. Companies
      Atmel AT77C104B
      Authentec AES2510
      Validity Fingerprint sensor VFS301
      Fujitsu MBF 200
      Bio-Key biometrics solutions
      Notebooks
      Peripheral accessories USB drives
      Safes
      Time attendance
      Cars
      PDAs phone etc
    • 16. References
      1) http://www.biometrics.gov/Documents/biofoundationdocs.pdf
      2) http://www.biometrics.gov/Documents/BioHistory.pdf
      3) http://pagesperso-orange.fr /fingerchip /biometrics /types/fingerprint.htm
      4) A. Jain, "Biometrics: A grand challenge," Proceedings - International Conference on Pattern Recognition, vol. 2, pp. 935, 2004
      5) S. Hiratsuka, “The intelligent fingerprint authentication system SecureFinger,” NEC RESEARCH AND DEVELOPMENT, vol. 43, pp. 11, 2002
      6) J. Mainguet, "Fingerprint recognition based on silicon chips,” Future Generation Computer Systems” vol. 16, pp 403–415, (2000)
      7) Ji-Song Han,“Thermal Analysis of Fingerprint Sensor Having a Microheater Array, ” Department of Micro System Engineering, Nagoya University
      8) MitraDamghanian, “Analysis and design of a wide micro beam as a pressure gauge for high sensitivity MEMS fingerprint sensors” MicrosystTechnol, 2009

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