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Thesis

Quantifying the strength of evidence in forensic fingerprints

Abstract:

Part I presents a model for fingerprint matching using Bayesian alignment on unlabelled point sets. An efficient Monte Carlo algorithm is developed to calculate the marginal likelihood ratio between the hypothesis that an observed fingerprint and fingermark pair originate from the same finger and the hypothesis that they originate from different fingers. The model achieves good performance on the NIST-FBI fingerprint database of 258 matched fingerprint pairs, though the computed likelihood...

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Oxford college:
Somerville College
Role:
Author

Contributors

Role:
Supervisor
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
Language:
English
Keywords:
Subjects:
UUID:
uuid:0915280a-22cc-429d-90dc-77f934d61dde
Local pid:
ora:9151
Deposit date:
2014-10-21

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