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Fingerprint Recognition

Presented By:
Ranjit R, Banshpal
Outline
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Introduction to biometrics
Fingerprint
What is Fingerprint Recognition?
Fingerprint recognition system
Advantages
Disadvantages
Applications
Conclusion
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.
Physiological characteristics :
 Fingerprint
 face recognition
 DNA
 palm print
 hand geometry
 iris recognition(which has largely replaced retina)
 Odour /scent.

Behavioral characteristics :
 Gait
 voice
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.
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.
• 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
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.
• 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).
Fig 3.Verification vs. Identification
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
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.
Fig 5.Minutia extractor
• 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.
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.
ADVANTAGES
Very high accuracy.
Easy to use.
Small storage space required for the
biometric template.
DISADVANTAGES
Dirt , grime and wounds .
Placement of finger.
Can be spoofed .
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)
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.
Fingerprint recognition

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Fingerprint recognition

  • 2. Outline • • • • • • • • Introduction to biometrics Fingerprint What is Fingerprint Recognition? Fingerprint recognition system Advantages Disadvantages Applications Conclusion
  • 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. Physiological characteristics :  Fingerprint  face recognition  DNA  palm print  hand geometry  iris recognition(which has largely replaced retina)  Odour /scent. Behavioral characteristics :  Gait  voice
  • 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. 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. • 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. 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. • 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. Fig 3.Verification vs. Identification
  • 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. 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.
  • 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. 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. ADVANTAGES Very high accuracy. Easy to use. Small storage space required for the biometric template.
  • 17. DISADVANTAGES Dirt , grime and wounds . Placement of finger. Can be spoofed .
  • 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. 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.