Hybrid Fingerprint Recognition Using Minutiae and Shape

Asker Bazen*, Raymond Veldhuis, Sabih Gerez

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

1 Citation (Scopus)


This chapter presents a novel minutiae matching method that uses a thin-plate spline model to describe elastic distortions in fingerprints. The thin-plate spline model is estimated using a local and a global matching stage. After registration of the fingerprints according to the estimated model, the number of matching minutiae can be counted using very tight tolerance boxes. For deformed fingerprints, the algorithm gives considerably higher matching scores compared to rigid matching algorithms, while only taking 100 ms on a 1GHz P-III machine. The additional step of shape matching after elimination of the elastic deformations helps to reduce the error rates further. Furthermore, it is shown that the observed deformations are different from those described by theoretical models proposed in the literature. This chapter is an extension of earlier work that is reported in [1].

Original languageEnglish
Title of host publicationComputer-Aided Intelligent Recognition Techniques and Applications
EditorsMuhammad Sarfraz
Number of pages12
ISBN (Electronic)9780470094167
ISBN (Print)9780470094143
Publication statusPublished - 20 Dec 2005


  • Elastic distortions
  • Elastic distortions of fingerprints
  • Elastic minutiae matching algorithm
  • Global minutiae matching
  • Local minutiae matching
  • Minutiae extraction algorithms
  • Minutiae matching method
  • Shape matching


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