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Introduction to Fingerprint Biometrics

Introduction to Fingerprint Biometrics. By Tamar Bar. Why use biometrics?. · Biometric templates are unique to an individual. · Unlike password, pin number, or smart card, they cannot be forgotten, misplaced lost or stolen.

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Introduction to Fingerprint Biometrics

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  1. Introduction to Fingerprint Biometrics By Tamar Bar

  2. Why use biometrics? ·Biometric templates are unique to an individual. ·Unlike password, pin number, or smart card, they cannot be forgotten, misplaced lost or stolen. ·The person trying to access is recognized by his ID- represented by his unique biometric signature.

  3. Why use Fingerprint as a biometric? • Fingerprint scanning has a high accuracy rate. • Fingerprint authentication is a good choice for in-house systems. • scanners are small, ease of integration - can be easily adapted to keyboards. • Relatively low costs make it an affordable, simple choice for workplace access security. • The most common and oldest biometric used. • Fingerprints are credited as reliable in a court of law.

  4. Fingerprint basic terms • Ridges • Furrows • Minutiae Points • Whorl • Arch • Loop

  5. Samples of Minutiae points

  6. Identification Vs. Verification • one-to-one comparison - Identification and recognition are, essentially synonymous terms. In both processes, a sample is presented to the biometric system during enrollment. The system then attempts to find out who the sample belongs to, by comparing the sample with a database of samples in the hope of finding a match. • one-to-many comparison - Verification process is when the biometric system attempts to verify an individual's identity. Identification and recognition involve matching a sample against a database of many, whereas verification involves matching a sample against a database of one.

  7. Fingerprint Processing Stages • Scanning: (acquisition, capture)- Optical Method- Semiconductor generated electric field • Processing: -Specific image enhancing algorithms – improving the image.-Using Image processing operators to recognize patterns in the image.- all the “patterns” recognized by the operators and constructing a new entity representing the sample this entity can be a collection of the objects from the image. • Matching: comparing of the 2 samplestwo well known matching techniques are Minutiae Point comparison and Correlation (of the grayscale component values).- Minutiae Point - has problem with global pattern of ridges and furrows.- Correlation - requires precise location and affected by image translation and rotation. • Decision - match/ non-match result

  8. Search Methods for Fingerprint Identification Using Classification • Tree Structure • Hashing

  9. Accuracy and Integrity • false negatives are more likely to occur than false positives – good for highly secure system less for a costumer serving type of system. • presenting a fake sample – has solutions like measuring temperature, blood-oxygen level, pulse, blood flow, humidity heart rate & temp. • Technical problems - dirty scanner.

  10. Discussion Point • What types of systems really need biometrics as a security systems • Dangers in using personal bodily assets:- harming people to get hold of that assets.- forging profs that are court admissable- privacy issues.

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