Your SlideShare is downloading. ×
Biometrics
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Biometrics

3,242

Published on

it's all about biometrics authentication.....

it's all about biometrics authentication.....

Published in: Technology
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
3,242
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
359
Comments
0
Likes
2
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. 8/5/2009
    1
    BIOMETRICAUTHENTICATION
    By
    07BCE095
    DIVYA SHAH
  • 2. Contents – biometric systems
    Biometric identifiers
    Classification of biometrics methods
    Bio Introduction
    metric system architecture
    Performance evaluation
    Signature recognition
    Voice recognition
    Retinal scan
    Iris scan
    Face-scan and facial thermo gram
    Hand geometry
    8/5/2009
    2
  • 3. Personal identification objects
    • Token-based: “something that you have”
    • 4. Knowledge-based: “something that you know”
    • 5. Biometrics-based: “something that you are”
    8/5/2009
    3
  • 6. Definition of Biometrics
    Any automatically measurable, robust and
    distinctive physical characteristic or personal
    trait that can be used to identify an individual or verify the claimed identity
    of an individual.
    8/5/2009
    4
    Biometrics is the automatic recognition of
    a person using distinguishing traits
  • 7. Some applications
    • Financial security
    • 8. Physical access control,
    • 9. Benefits distribution,
    • 10. Customs and immigration,
    • 11. National ID systems,
    • 12. Voter and driver registration,
    • 13. Telecommunications
    8/5/2009
    5
  • 14. Biometric identifiers
    8/5/2009
    6
  • 21. Classification of biometrics methods
    Static
    8/5/2009
    7
    Dynamic
    • signature recognition
    • 25. speaker recognition
  • Biometric system architecture
    8/5/2009
    8
  • 31. Biometric system model
    8/5/2009
    9
  • 32. Data acquisition module
    • Reads the biometric info from the user.
    • 33. Examples: video camera, fingerprint scanner/sensor, microphone, etc.
    • 34. All sensors in a given system must be similar to ensure recognition at any location.
    • 35. Environmental conditions may affect their performance.
    8/5/2009
    10
  • 36. Feature extraction module
    • Discriminating features extracted from the raw biometric data.
    • 37. Raw data transformed into small set of bytes – storage and matching.
    • 38. Various ways of extracting the features.
    • 39. Pre-processing of raw data usually necessary.
    8/5/2009
    11
  • 40. Matching module
    • The core of the biometric system.
    • 41. Measures the similarity of the claimant’s sample with a reference template.
    • 42. Typical methods: distance metrics, probabilistic measures, neural networks, etc.
    • 43. The result: a number known as match score.
    8/5/2009
    12
  • 44. Storage module
    • Maintains the templates for enrolled users.
    • 45. One or more templates for each user.
    • 46. The templates may be stored in:
    • 47. a special component in the biometric device,
    • 48. conventional computer database,
    • 49. portable memories such as smartcards.
    8/5/2009
    13
  • 50. Possible decision outcomes
    • A genuine individual is accepted.
    • 51. A genuine individual is rejected (error).
    • 52. An impostor is rejected.
    • 53. An impostor is accepted (error).
    8/5/2009
    14
  • 54. Biometric technologies
    8/5/2009
    15
  • 60. Signature recognition
    Variety of characteristics can be used
    angle of the pen
    pressure of the pen
    total signing time
    velocity and acceleration
    geometry
    8/5/2009
    16
  • 61. Fingerprint recognition
    • Ridge patterns on fingers uniquely identify people.
    • 62. Classification scheme devised in 1890s.
    • 63. Major features: arch, loop, whorl.
    • 64. Each fingerprint has at least one of the major features and many ‘small’ features.
    8/5/2009
    17
  • 65. Eye biometric
    8/5/2009
    18
    Iris
    • colored portion of the eye surrounding the pupil.
    • 66. complex iris pattern used for identification.
    Retina
    • Back inside of the eye ball.
    • 67. Pattern of blood vessels used for identification.
  • Speaker recognition
    • Linguistic and speaker dependent acoustic patterns.
    • 68. Speaker’s patterns reflect:
    • 69. anatomy (size and shape of mouth and throat),
    • 70. behavioral (voice pitch, speaking style).
    • 71. Heavy signal processing involved (spectral analysis, periodicity, etc)
    8/5/2009
    19
  • 72. Face-scan and Facial Thermograms
    • Static controlled or dynamic uncontrolled shots.
    • 73. Visible spectrum or infrared (thermo grams).
    • 74. Non-invasive, hands-free, and widely accepted.
    • 75. Questionable discriminatory capability.
    8/5/2009
    20
  • 76. Hand geometry
    • Features:
    Dimensions and shape of the hand, fingers, and knuckles as well as their relative locations.
    • Two images taken: One from the top and one from the side.
    8/5/2009
    21
  • 77. 8/5/2009
    22
    Thank you

×