Presented byShree Prakash   M.Tech(R)  611CS106
INTRODUCTION• Fingerprint is most popular,reliable and oldest  biometric sign of identity• Touchless fingerprint system is...
FINGERPRINT PATTERN1) ARCH(a) Plain(b)Tented2) LOOP(c)Left(d)Right(e)Twin3)    WHORL
TERMINOLOGY• Fingerprint can be looked at from different  levels1) GLOBAL LEVEL• Singularity points called core and delta ...
2) LOCAL LEVELMinutiae details in terms of ridgesRidge bifurcation    Ridge termination    Representation of minutiae
3) VERY FINE LEVELFinger sweat pores
TOUCHLESS VERSUS TOUCH-BASED                       TOUCHLESS   TOUCH-BASED SKIN DISTORTION         NO           YES SLIPPA...
FINGERPRINT RECOGNITION SYSTEMA.   IMAGE ACQUISITIONB.   PREPROCESSINGC.   FEATURE EXTRACTIOND.   MATCHING
IMAGE ACQUISITION                                 MULTIPLE VIEW SYSTEMFigure 1.   Fingerprint acquisition using a set of c...
• Multiple view enables the capture of full nail  to nail fingerprints increasing the usable area• From each acquired imag...
Figure 2   Fingerprint acquisition obtained by combining a single           line scan camera and two mirrors
3D FINGERPRINT UNWRAPPING• Unwrapping a 3D object refers to the unfolding  the 3D object onto a flat 2D plane.            ...
PARAMETRIC UNWRAPPING USING          CYLINDRICAL MODEL• Human fingers vary in shape, like the shape of the  middle finger ...
T           Parametric unwrapping using a cylindrical model (top           down view). Point (x,y,z) on the 3D finger is p...
• Mathematically, let the origin be positioned at  the bottom of the finger, centered at the  principle axis of the finger...
• This 3D point is then projected (transformed)  onto the cylindrical surface to obtain the  corresponding 2D coordinates ...
NON PARAMETRIC -UNWRAPPING• Non-parametric unwrapping, does not involve  any projection on parametric models.• The unwrapp...
COMPARISIONPARAMETRIC UNWRAPPING   UNPARAMETIC WNRAPPING
PREPROCESSING STEPSa) Computation of local ridge frequency and local   ridge orientationb) Enhancement of the fingerprint ...
FINGERPRINT MATCHING• MINUTIAE-BASED APPROACH :- Analogous with  the way that forensic experts compare  fingerprints• The ...
DISADVANTAGE• Lower contrast between ridges and valleys  due to motion blur of hand tremble , camera  background noise and...
REFERENCE• Intelligent biometrics technique in finger print and  face recognition by L.C Jain, U.halice, S.B lee,S.T  Suts...
Touchless fingerprint
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Touchless fingerprint

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Touchless fingerprint

  1. 1. Presented byShree Prakash M.Tech(R) 611CS106
  2. 2. INTRODUCTION• Fingerprint is most popular,reliable and oldest biometric sign of identity• Touchless fingerprint system is a remote sensing technique to process fingerprint pattern, considered as a viable alternative to touch based fingerprint system• New generation of touchless live scan devices is 3D touchless finger print system
  3. 3. FINGERPRINT PATTERN1) ARCH(a) Plain(b)Tented2) LOOP(c)Left(d)Right(e)Twin3) WHORL
  4. 4. TERMINOLOGY• Fingerprint can be looked at from different levels1) GLOBAL LEVEL• Singularity points called core and delta points Core and delta points marked on sketches of the two fingerprint patterns loop and whorl
  5. 5. 2) LOCAL LEVELMinutiae details in terms of ridgesRidge bifurcation Ridge termination Representation of minutiae
  6. 6. 3) VERY FINE LEVELFinger sweat pores
  7. 7. TOUCHLESS VERSUS TOUCH-BASED TOUCHLESS TOUCH-BASED SKIN DISTORTION NO YES SLIPPAGE,SMEARING NO YES FINGERPRINT RESIDUE NO YES CAPTURE AREA LARGE SMALL TOLERANCE ON SKIN CONDITION LARGE SMALL HIGH LOWUSER COMFORT LEVEL
  8. 8. FINGERPRINT RECOGNITION SYSTEMA. IMAGE ACQUISITIONB. PREPROCESSINGC. FEATURE EXTRACTIOND. MATCHING
  9. 9. IMAGE ACQUISITION MULTIPLE VIEW SYSTEMFigure 1. Fingerprint acquisition using a set of cameras surrounding the finger
  10. 10. • Multiple view enables the capture of full nail to nail fingerprints increasing the usable area• From each acquired image a silhouette is extracted.• The 5 silhouettes are then projected into the 3D space and we get the 3D shape of finger by knowing the position and orientation of each camera within a reference coordinate system.
  11. 11. Figure 2 Fingerprint acquisition obtained by combining a single line scan camera and two mirrors
  12. 12. 3D FINGERPRINT UNWRAPPING• Unwrapping a 3D object refers to the unfolding the 3D object onto a flat 2D plane. UNWRAPPING METHOD PARAMETRIC NON PARAMETRIC
  13. 13. PARAMETRIC UNWRAPPING USING CYLINDRICAL MODEL• Human fingers vary in shape, like the shape of the middle finger is often more cylindrical than the thumb.• Human fingers can be closely approximated by cylinders.• Human fingers also vary in size and the cylindrical model can also capture this size variability in the vertical direction, but not in the horizontal direction.• Cylindrical model is a reasonable choice for parametric unwrapping of3D fingerprints.
  14. 14. T Parametric unwrapping using a cylindrical model (top down view). Point (x,y,z) on the 3D finger is projectedFigure 3 to ( ,z) on the 2D plane.
  15. 15. • Mathematically, let the origin be positioned at the bottom of the finger, centered at the principle axis of the finger.• Let T be a point on the surface of the 3D finger: x T = Y z
  16. 16. • This 3D point is then projected (transformed) onto the cylindrical surface to obtain the corresponding 2D coordinates S = z Where
  17. 17. NON PARAMETRIC -UNWRAPPING• Non-parametric unwrapping, does not involve any projection on parametric models.• The unwrapping directly applies to the object to preserve local distances or angular relations.• Guarantees the variability in both shape and size of fingers is preserved.• Less distortion compared to parametric unwrapping
  18. 18. COMPARISIONPARAMETRIC UNWRAPPING UNPARAMETIC WNRAPPING
  19. 19. PREPROCESSING STEPSa) Computation of local ridge frequency and local ridge orientationb) Enhancement of the fingerprint imagec) Segmentationd) Detection of singularities FEATURE EXTRACTIONa) Conversion of preprocessed fingerprint image into binary imageb) Thinning
  20. 20. FINGERPRINT MATCHING• MINUTIAE-BASED APPROACH :- Analogous with the way that forensic experts compare fingerprints• The minutiae sets of the two fingerprints to be compared are first aligned, requiring displacement and rotation to be computed• Region of tolerance around the minutiae position is defined in order to compensate for the variations that may appear in the minutiae position due to noise and distortion
  21. 21. DISADVANTAGE• Lower contrast between ridges and valleys due to motion blur of hand tremble , camera background noise and small depth of field• Unwrapping technique has distortion upto some extent• Compatibility with contact-based 2D rolled fingerprint image
  22. 22. REFERENCE• Intelligent biometrics technique in finger print and face recognition by L.C Jain, U.halice, S.B lee,S.T Sutsui,I.Hayashi• Tabassi E., Wilson C., and Watson C., “Fingerprint Image Quality,” Tech. Rep. 7151, National Institute of Standards and Technology (NIST), August 2004.• Parziale G. and Diaz-Santana E., “The Surround Imager: Multi-Camera Touchless Device to Acquire 3D Rolled- Equivalent Fingerprints,” in Proceedings of IAPR International Conference on Biometrics (ICB),Hong Kong, China, January 2006, pp. 244–250.
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