Nonparametric Fingerprint Deformation Modelling

  • Neil Yager
  • Adnan Amin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3691)


This paper presents a novel approach to modelling fingerprint deformations. When fingerprints are captured, they undergo a certain amount of distortion due to the application of a three dimensional elastic tissue against a flat surface. This poses a challenge for automated fingerprint verification systems, which are generally based on aligning two fingerprints and comparing their respective features. There are only a few methods reported in the literature for modelling fingerprint distortions. One prominent method is based on using minutiae correspondences as landmarks, and creating a deformation model using thin-plate splines. There are several disadvantages to this approach, and a nonparametric elastic modelling algorithm is developed in this paper to address these issues. Both algorithms have been implemented and are evaluated by incorporating them into a fingerprint verification system. The results show an improvement of the proposed algorithm over the existing method of deformation modelling.


Query Image Deformation Modelling Equal Error Rate Distortion Modelling Fingerprint Match 
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-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Neil Yager
    • 1
  • Adnan Amin
    • 1
  1. 1.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia

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