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Application of Spatial Statistics to Latent Print Identifications: Towards Improved Forensic Science Methodologies

NCJ Number
Date Published
November 2012
109 pages
This final report presents the results of a study that investigated the question of fingerprint uniqueness by statistically evaluating the spatial distribution of fingerprint ridgeline features.
The objectives of this study were twofold: to spatially analyze fingerprint features using geographic information systems (GIS) techniques, and to develop probabilities to provide a quantitative measure of the discriminating value of fingerprint ridgeline features. The parameters of the fingerprint ridgeline features included minutiae location, direction, and minutiae ridgeline configurations. Data for the study were obtained from a dataset of digitized fingerprints from the population in Oregon that were spatially analyzed using GIS software. Results from the GIS-based spatial characterization part of the study include the following: GIS techniques can be used to spatially analyze fingerprint patterns; a variety of analytical tools can be developed to characterize fingerprint features and statistically characterize distributions between pattern types; and minutiae and ridgelines were found to be most densely packed in the region below the core, with the greatest ridgeline-length density surrounding the core. Geometric morphometric analyses were also used in the research to study the shape variations of four fingerprint pattern types with the intent to determine the extent and degree of variation within and among four fingerprint pattern types. The results of these analyses are discussed in the report. The third part of the research used Monte Carlo simulations to calculate random-match probabilities to evaluate the spatial configurations of minutiae within and between pattern types. Implications for policy and practice are discussed. Tables, figures, references, and appendixes

Date Published: November 1, 2012