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

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

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

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

15. Uniqueness

16. Stability

17. Collectability

18. Performance

19. Acceptability

20. Forge resistance8/5/2009 6

22. retinal scan

23. iris scan

26. Data acquisition

27. Feature extraction

28. Matching

29. Decision

30. Storage8/5/2009 8

31. Biometric system model 8/5/2009 9

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

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

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

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

51. A genuine individual is rejected (error).

52. An impostor is rejected.

53. An impostor is accepted (error).8/5/2009 14

55. Voice recognition

56. Retinal scan

57. Iris scan

58. Face biometrics

59. Hand geometry8/5/2009 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

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

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

73. Visible spectrum or infrared (thermo grams).

74. Non-invasive, hands-free, and widely accepted.

75. Questionable discriminatory capability.8/5/2009 20

77. 8/5/2009 22 Thank you