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Fingerprint Analysis: Parametric and Nonparametric Models

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If you have a question about this talk, please contact Carola-Bibiane Schoenlieb .

Fingerprint analysis for forensic and security related applications relies on global features such as the orientation field and local features such as minutiae patterns. Here the ultimate goal would be to extract from a high-dimensional finger’s imprint image bitmap a low-dimensional feature vector that is robust against Euclidean motions and noise such as local distortions. For the orientation field we propose a parametric model based on quadratic differentials and for minutiae patterns a non-parametric model based on histogram counts.

This talk is part of the Cambridge Image Analysis Seminars series.

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