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Statistical Modelling of Fingerprints

Llewelyn, Stephanie Jane (2014) Statistical Modelling of Fingerprints. PhD thesis, University of Sheffield.

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It is believed that fingerprints are determined in embryonic development. Unlike other personal characteristics the fingerprint appears to be a result of a random process. For example fingerprints of identical twins (whose DNA is identical) are distinct, and extensive studies have found little evidence of a genetic relationship in terms of types of fingerprint, certainly at the small scale. At a larger scale the pattern of ridges on fingerprints can be categorised as belonging to one of five basic forms: loops (left and right), whorls, arches and tented arches. The population frequencies of these types show little variation with ethnicity and a list of the types occurring on the ten digits can be used as an initial basis for identification of individuals. However, such a system would not uniquely identify an individual although the frequency of certain combinations could be extremely small. At a smaller scale various minutiae or singularities can be observed in a fingerprint. These include ridge endings and bifurcations, amongst others. Typical fingerprints have several hundred of these as well as two key points (with the exception of a simple arch) referred to as the core and delta, which are focal points of the overall pattern of ridges. Modern identification systems are based upon ridge endings and bifurcations, not least because they are the easiest to determine automatically from image analysis. The configuration of these minutiae is unique to the individual. This research explores the relationship between the locations of minutiae to determine if they can be modelled using a statistical process. In addition, since the approach is based on how fingerprints can be examined in a forensic situation an algorithm is created and tested which allows the strength of a match between a fingermark left at a crime and a fingerprint from a known suspect to be calculated. Currently the result of matching a fingermark and fingerprint is expressed as a categorical value of; match, no match or inconclusive. The method in this research allows this to be expressed as a numerical value allowing for a wider and more flexible use of fingerprint evidence.

Item Type: Thesis (PhD)
Keywords: Statistics, Fingerprints, Forensics, Bayesian, Likelihood Ratio, Spatial, Point Patterns
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield)
Identification Number/EthosID: uk.bl.ethos.632993
Depositing User: Miss Stephanie Jane Llewelyn
Date Deposited: 14 Jan 2015 15:14
Last Modified: 03 Oct 2016 12:08
URI: http://etheses.whiterose.ac.uk/id/eprint/7722

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