03 - General biometric facts

Overview

  • Description:: continuation about general things on biometric systems

Enrollment vs Recognition

  • Enrollment: capture and processing of user biometric data for use by system in subsequent authentication operations (gallery)
  • Recognition: capture and processing of user biometric data in order to rendere an authentication decision based on the outcome of a matching process of the stored to current template.

Phases

A Conventional sample is what we capture (signal) such as heartbeat while using a smartwatch. This phase is called Acquisition. Feature acquisition is what we are interested in. These features are collected in Feature Vector (identity) is stored in a Template. The template will be in the template archive.

Modules

  1. Sensor module: where biometric data are caught
  2. Feature extraction module: where a set of main characteristic is extracted from acquired data
  3. Matching module: extracted feature are matched with stored template to return one or more matching stores
  4. Decision module: who pass and who not

Users and experiments

  • cooperative: the user is interested in being recognized

  • non-cooperative: the opposite

  • public/private: users of the system are customers of the entity installing the system

  • used/non used: frequency of use of the biometric system

  • aware/not aware: the user is aware or not of the recognition process

  • experiments could be executed in:

    • controlled environment: capture settings can be controlled. Capture could be repeated.
    • uncontrolled/undercontrolled environment: it cannot. So template could present several levels of distortion. Templates can be rejected, but capture cannot be repeated

Verification vs Identification

  • verification: the user claims an identity, and the system checks if it matches the identity

  • identification: no claims from the user, the system determines who the user is through gallery

  • open set: the system determines if probe belongs to a subject in the gallery G

    • possible error: reject a probe belonging to an enrolled subject
  • closed set: all probes belong to enrolled subjects

    • possible error: return the wrong identity

Feature / traits

  • universality: the trait must be owned by any person
  • uniqueness: any pair of people should be different according to the biometric trait
  • permanence: trait should not be change in time
  • collectability: should be measurable by some sensor
  • acceptability: involved people should not have any objection to allowing collection / measurement of the trait

Good traits: fingerprints biometry, eye biometry - iris and retina, face biometry (photo, infrared), ear biometry, hand biometry, signature biometry (signature recognition) still and dynamic, keys typing, voice biometry, DNA

Verification vs authenticaion

if a system asks for an implicit or an explicit claim, then it’s verification when there is only one stored subject, then it’s verification

when a system store more identities, we cannot say whether is authentication or verification

if it’s up to the system to identify whether the template probed matches the stored template → identification

if a system asks for a password or pincode or whatever and then for a fingerprint ‚Üí verification