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Thursday, 27 September 2018

Biometric technology ,Introduction,Types,Features,and its Uses

Biometric Technology Introduction,Types,Features,and Its Uses

Bio Metric Machine

What are Biometrics:


  • The term "biometrics" is derived from the Greek
    words bio (life) and metric (to measure).
  • For our use, biometrics refers to technologies for
    measureing and analyzing 
    physiological or behavioral characteristics .
    Features are unique 
    could be used to verify or identify a person.

Problems with current security
systems

  1. Based on Passwords, or ID / Swipe cards
  2.  Can be Lost.
  3.  Can be forgotten
  4.  Worse! Can be stolen and used by a thief / intruder to access your data, bank accounts, car etc.

Problems with current securitysystems


  • With increasing use of IT technology and need to protect data,we have multiple accounts/passwords.
  • We can only remember so many passwords, so we end up using things we know to create them (birthdays, wife/girlfriends name, dog, cat…).
  • Its is easy to crack passwords, because most of our passwords are weak!
  • If we create strong passwords (that should be meaningless to us) we will forget them! And there is no way to remember multiple such passwords.

Examples of Different Biometrics:

Diffrent types of Biometric


  • Face
  • • Fingerprint
  • • Voice
  • • Palmprint
  • • Hand Geometry
  • • Iris
  • • Retina Scan
  • • Voice
  • • DNA
  • • Signatures
  • • Gait
  • • Keystroke

Applications + Terminology:

Identification:
  • Match a person’s biometrics against a database to figure out his identity by finding the closest match. 
  • Commonly referred to as 1:N matching .
  • ‘Criminal Watch-list’ application scenarios.
Verification:
  • The person claims to be 'John', system must match and compare his / her biometrics with John's stored Biometrics.
  • If they match, then user is 'verified' or authenticated that he is indeed 'John'.
  • Access control application scenarios
  • Typically referred as 1: 1 matching.

Minutiae based fingerprint Matching

  • This is one of the most commonly used algorithms for extracting features that characterizes a fingerprint
  • The different Minutia feature locations and types identifying different persons.
  • These are stored in the biometric template.
  • Image & Signal processing used to process fingerprint images.

Fingerprint Sensors

Different Fingerprint Sensors:

Optical Sensors
  • Optic reflexive
  • Optic Transmissive
  • Fiber Optic Plate
Capacitive / Semiconductor Sensors
  • Static Capacitive I, II
  • Dynamic Capacitive
Ultrasound sensors


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