Computation of likelihood ratios in fingerprint identification for configurations of three minutiæ

Cedric Neumann, Christophe Champod*, Roberto Puch-Solis, Nicole Egli, Alexandre Anthonioz, Didier Meuwly, Andie Bromage-Griffiths

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Recent challenges to fingerprint evidence have brought forward the need for peer-reviewed scientific publications to support the evidential value assessment of fingerprint. This paper proposes some research directions to gather statistical knowledge of the within-source and between-sources variability of configurations of three minutiæ on fingermarks and fingerprints. This paper proposes the use of the likelihood ratio (LR) approach to assess the value of fingerprint evidence. The model explores the statistical contribution of configurations of three minutiae using Tippett plots and related measures to assess the quality of the system. Features vectors used for statistical analysis have been obtained following a preprocessing step based on Gabor filtering and image processing to extract minutia position, type, and direction. Spatial relationships have been coded using Delaunay triangulation. The metric, used to assess similarity between two feature vectors is based on an Euclidean distance measure. The within-source variability has been estimated using a sample of 216 fingerprints from four fingers (two donors). Between-sources variability takes advantage of a database of 818 ulnar loops from randomly selected males. The results show that the data-driven approach adopted here is robust. The magnitude of LRs obtained under the prosecution and defense propositions stresses upon the major evidential contribution that small portions of fingermark, containing three minutiæ, can provide regardless of its position on the general pattern.

Original languageEnglish
Pages (from-to)1255-1266
Number of pages12
JournalJournal of Forensic Sciences
Issue number6
Publication statusPublished - 1 Nov 2006


  • Fingermark
  • Fingerprint
  • Forensic science
  • Identification
  • Individualization
  • Likelihood ratio
  • Statistics


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