Fingerprint%20Analysis

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• Fingerprint Analysis
• (part 2)
• Pavel Mrázek

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Local ridge frequency
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Local ridge frequency
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Image enhancement / binarization

• General rule
• Smooth along ridges
• Enhance ridge-valley contrast
• Separate fingerprint from background(segmentation
  )
• Various methods
• Convolution
• PDEs
• Morphology
• Gabor filters

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Gabor filters

• Several orientations
• Several frequencies
• At each position,
• select orientation
• select frequency
• filter using the appropriate Gabor filter

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Gabor filters
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Coherence enhancing shock filter

• Shock filter
• Regularized

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Coherence enhancing shock filter

• Use direction estimatew dominant eigenvector
  of the structure tensor

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Coherence enhancing shock filter

• Examples

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Ridge thinning

• Thinning morphological operation
• Pixel value set to background if ridge
  connectivity not affected
• Structuring element typically 3x3 window
• 9 pixels, 512 possible configurations, look-up

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Singular point detection

• Methods for core and delta detection
• Poincaré index
• Irregularity of orientation field, curvature
• Partitioning of orientation field
• Reliability problems

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Texture features
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Feature extraction summary

• Extract features, store a template
• Prepare representation useful for matching
• minutiae
• Reduce memory requirements(typical size 500 B
  30 kB)
• Privacy fingerprint not stored

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Enrollment

• Register user, store data into a database

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Verification

• Compare to enrolled template,accept / reject a
  match

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Identification

• Recover identity, 1-to-N match

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References

• Maltoni et al. Handbook of Fingerprint
  Recognition. Springer 2003.
• Maltoni. A tutorial on fingerprint recognition.
  In LNCS 3161, Springer 2005.
• Hong, Wan, Jain. Fingerprint image enhancement
  algorithm and performance evaluation. IEEE PAMI
  1998.
• Zhou, Gu. A model-based method for the
  computation of fingerprints orientation field.
  IEEE TIP 2004.
• Weickert. Coherence enhancing shock filters. DAGM
  2003.
• Contact mrazekp -at- cmp.felk.cvut.cz