A wavelet-based approach to ridge thinning in fingerprint images

Xinge You*, Bin Fang, Yuan Yan Tang, Zhenyu He

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

2 Citations (Scopus)


As a global feature of fingerprints, the thinning of ridges, extraction of minutiae and computation of orientation field are very important for automatic fingerprint recognition. Many algorithms have been proposed for their computation and estimation, but their results are unsatisfactory, especially for poor quality fingerprint images. In this paper, a robust wavelet-based method to create thinned ridge map of fingerprint for automatic recognition is proposed. Properties of modulus minima based on the spline wavelet function are substantially investigated. Desirable characteristics show that this method is suitable to describe the skeleton of the ridge of the fingerprint image. A multi-scale thinning algorithm based on the modulus minima of wavelet transform is presented. The proposed algorithm is able to improve the skeleton representation of the ridge of the fingerprint without side-effects and limitations of the existing methods. The thinned ridge map can facilitate the extraction of the minutiae for matching in fingerprint recognition. Experiments have been conducted to validate the effectiveness and efficiency of the proposed method.

Original languageEnglish
Pages (from-to)631-645
Number of pages15
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Issue number5
Publication statusPublished - Aug 2005

Scopus Subject Areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

User-Defined Keywords

  • Wavelet transform
  • fingerprint
  • thinned ridge
  • directional field


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