Fingerprint recognition


Published on

Published in: Technology
No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Fingerprint recognition

  1. 1. Fingerprint Recognition Presented By: Ranjit R, Banshpal
  2. 2. Outline • • • • • • • • Introduction to biometrics Fingerprint What is Fingerprint Recognition? Fingerprint recognition system Advantages Disadvantages Applications Conclusion
  3. 3. Biometrics • Biometrics is the science and technology of measuring and analyzing biological data • Biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns ,facial patterns and hand measurements, for authentication purposes. • The two categories of biometric identifiers include :  physiological characteristics.  behavioral characteristics.
  4. 4. Physiological characteristics :  Fingerprint  face recognition  DNA  palm print  hand geometry  iris recognition(which has largely replaced retina)  Odour /scent. Behavioral characteristics :  Gait  voice
  5. 5. Fingerprint • A fingerprint is the feature pattern of one finger. • It is the pattern of ridges and valleys (also called furrows in the fingerprint literature) on the surface of a fingertip. • Each individual has unique fingerprints so the uniqueness of a fingerprint is exclusively determined by the local ridge characteristics and their relationships • These local ridge characteristics are not evenly distributed.
  6. 6. Fig 1. A fingerprint image acquired by an Optical Sensor • • Fingerprints are distinguished by Minutiae, which are some abnormal points on the ridges. The two most prominent local ridge characteristics, called minutiae, are 1) ridge ending and 2) ridge bifurcation.
  7. 7. • A ridge ending is defined as the point where a ridge ends abruptly. • A ridge bifurcation is defined as the point where a ridge forks or diverges into branch ridges. Fig 2.ridge and valley
  8. 8. What is Fingerprint Recognition? • Fingerprint recognition (sometimes referred to as dactyloscopy) is the process of comparing questioned and known fingerprint against another fingerprint to determine if the impressions are from the same finger or palm.
  9. 9. • The fingerprint recognition problem can be grouped into two sub-domains:  Fingerprint verification : Fingerprint verification is to verify the authenticity of one person by his fingerprint.  Fingerprint identification: Fingerprint identification is to specify one person’s identity by his fingerprint(s).
  10. 10. Fig 3.Verification vs. Identification
  11. 11. FINGERPRINT RECOGNITION SYSTEM • Fingerprint recognition system operates in three stages: (i) Fingerprint acquiring device (ii) Minutia extraction and (iii) Minutia matching Fig 4. Fingerprint recognition system
  12. 12. 1.Fingerprint acquisition: For fingerprint acquisition, optical or semiconduct sensors are widely used. They have high efficiency and acceptable accuracy except for some cases that the user’s finger is too dirty or dry. 2.Minutia extractor : To implement a minutia extractor, a threestage approach is widely used by researchers which are  preprocessing  minutia extraction and  postprocessing stage.
  13. 13. Fig 5.Minutia extractor
  14. 14. • For the fingerprint image preprocessing stage:  Image enhancement  Image binarization  Image segmentation • The job of minutiae extraction closes down to two operations: Ridge Thinning, Minutiae Marking,. • In post-processing stage, false minutia are removed and bifurcations is proposed to unify terminations and bifurcations.
  15. 15. 3.Minutiae Matching: • Generally, an automatic fingerprint verification is achieved with minutia matching (point pattern matching)instead of a pixel-wise matching or a ridge pattern matching of fingerprint images. • The minutia matcher chooses any two minutia as a reference minutia pair and then match their associated ridges first. • If the ridges match well, two fingerprint images are aligned and matching is conducted for all remaining minutia.
  16. 16. ADVANTAGES Very high accuracy. Easy to use. Small storage space required for the biometric template.
  17. 17. DISADVANTAGES Dirt , grime and wounds . Placement of finger. Can be spoofed .
  18. 18. applications Banking Security - ATM security,card transaction Physical Access Control (e.g. Airport) Information System Security National ID Systems Passport control (INSPASS) Prisoner, prison visitors, inmate control Voting Identification of Criminals Identification of missing children Secure E-Commerce (Still under research)
  19. 19. Conclusion • The implemented minutia extraction algorithm is accurate and fast in minutia extraction. • The algorithm also identifies the unrecoverable corrupted regions in the fingerprint and removes them from further processing. • This is a very important property because such unrecoverable regions do appear in some of the corrupted fingerprint images and they are extremely harmful to minutiae extraction.