Fingerprint recognition is a biometric technique that uses fingerprint patterns to identify or verify individuals. It works by extracting minutiae points like ridge endings and bifurcations from scanned fingerprints and matching them against a database. The process involves fingerprint acquisition using optical or semiconductor sensors, minutiae extraction after preprocessing and thinning the image, and minutiae matching for verification or identification. Fingerprint recognition has applications in security systems and has advantages of high accuracy and small storage requirements, though it can be affected by dirty or wounded fingers.

1. Fingerprint Recognition
Presented By:
Ranjit R, Banshpal

2. Outline
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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
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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.

13. Fig 5.Minutia extractor

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.