Möbius Moduli for Fingerprint Orientation Fields

@article{Imdahl2017MbiusMF,
  title={M{\"o}bius Moduli for Fingerprint Orientation Fields},
  author={Christina Imdahl and Carsten Gottschlich and Stephan F. Huckemann and Ken'ichi Ohshika},
  journal={Journal of Mathematical Imaging and Vision},
  year={2017},
  volume={60},
  pages={651-660}
}
We propose a novel fingerprint descriptor, namely Möbius moduli, measuring local deviation of orientation fields (OF) of fingerprints from conformal fields, and we propose a method to robustly measure them, based on tetraquadrilaterals to approximate a conformal modulus locally with one due to a Möbius transformation. Conformal fields arise by the approximation of fingerprint OFs given by zero-pole models, which are determined by the singular points and a rotation. This approximation is very… 
An anisotropic interaction model for simulating fingerprints
TLDR
It is shown that fingerprint patterns can be modeled as stationary solutions by choosing the underlying Tensor field appropriately, and this dependence on the tensor field leads to complex, anisotropic patterns.
An anisotropic interactionmodel for simulating fingerprints
TLDR
It is shown that fingerprint patterns can be modeled as stationary solutions by choosing the underlying Tensor field appropriately, and this dependence on the tensor field leads to complex, anisotropic patterns.
Anisotropic nonlinear PDE models and dynamical systems in biology
This thesis was supported by the EPSRC, the MSCA-RISE projects CHiPS and NoMADS, the Cambridge Commonwealth, European & International Trust, the German Academic Scholarship Foundation, the Cambridge

References

SHOWING 1-10 OF 34 REFERENCES
Global Models for the Orientation Field of Fingerprints: An Approach Based on Quadratic Differentials
TLDR
The proposed quadratic differentials model for orientation fields of fingerprints allows for extrapolation into unobserved regions, and is able to verify analytically Penrose's formula for the singularities on a palm.
Perfect fingerprint orientation fields by locally adaptive global models
TLDR
An algorithm to perfectly estimate OF parameters automatically or semi-automatically, depending on image quality, is described, and the main underlying claim of high fidelity low parameter OF compression is established.
Robust Orientation Field Estimation and Extrapolation Using Semilocal Line Sensors
TLDR
A novel method for OF estimation that uses traced ridge and valley lines that provides robustness against disturbances caused, e.g., by scars, contamination, moisture, or dryness of the finger is presented.
Curved-Region-Based Ridge Frequency Estimation and Curved Gabor Filters for Fingerprint Image Enhancement
TLDR
Curved GFs are introduced that locally adapt their shape to the direction of flow and enable the choice of filter parameters that increase the smoothing power without creating artifacts in the enhanced image.
Separating the real from the synthetic: minutiae histograms as fingerprints of fingerprints
In this study we show that by the current state-of-the-art synthetically generated fingerprints can easily be discriminated from real fingerprints. We propose a method based on second order extended
Oriented diffusion filtering for enhancing low-quality fingerprint images
TLDR
A novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step is presented, showing its competitiveness with other state-of-the-art enhancement methods for fingerprints.
Towards generating realistic synthetic fingerprint images
TLDR
This paper has performed a test of realness comparing prints synthesized by RFC and real fingerprints, and it is observed that the proposed RFC is the first method which produces artificial fingerprints that pass this test due to their realistic minutiae configuration.
Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection
TLDR
A new type of local image descriptor is presented which yields binary patterns from small image patches which is expected to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, and machine vision for surface inspection and material classification.
Global variational method for fingerprint segmentation by three-part decomposition
TLDR
A novel segmentation method by global three-part decomposition (G3PD), based on global variational analysis, which decomposes a fingerprint image into cartoon, texture and noise parts and consistently outperforms existing methods in terms of segmentation accuracy.
Filter Design and Performance Evaluation for Fingerprint Image Segmentation
TLDR
A novel factorized directional band pass (FDB) segmentation method for texture extraction based on the directional Hilbert transform of a Butterworth bandpass (DHBB) filter interwoven with soft-thresholding is proposed.
...
...