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Enhancement of Fingerprint Images using Shape-Adapted Scale-Space Operators

  • Andrés Almansa
  • Tony Lindeberg
Part of the Computational Imaging and Vision book series (CIVI, volume 8)

Abstract

Automated Fingerprint Identification Systems (AFIS) rely on the ridge structure of a fingerprint for comparing it to other fingerprints in a database. The structure of current AFIS closely resembles the manual procedure used by human experts (McCabe et al., 1992), and can be briefly described as follows:
  • Enhance the fingerprint image. This usually involves a filtering step to suppress noise. The output from this step can be either a better grey-level image or a binary image in which the ridge structure of the original is preserved.

  • Extract the ridge structure of the fingerprint, i.e., build a graph-like representation of the skeletonized ridges and their incidence relations.

  • Classify the fingerprint according to its ridge structure at a coarse scale. This reduces the search space, thus speeding up the procedure.

  • Detect minutiae, i.e. singularities in the ridge structure, such as bifurcations and ridge endings. Then, build a feature vector of the fingerprint.

  • Store the feature vectors in a database for later use and/or search for fingerprints with matching feature vectors (which will most likely correspond to the same person).

Keywords

Integration Scale Fingerprint Image Shape Adaptation Scale Selection Ridge Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Andrés Almansa
    • 1
  • Tony Lindeberg
    • 2
  1. 1.Centro de Cálculo, Facultad de IngenieríaUniversidad de la RepúblicaMontevideoUruguay
  2. 2.Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science (NADA)KTH (Royal Institute of Technology)StockholmSweden

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