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Probabilistic evaluation of handwriting evidence: likelihood ratio for authorship
Author(s) -
Bozza Silvia,
Taroni Franco,
Marquis Raymond,
Schmittbuhl Matthieu
Publication year - 2008
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2007.00616.x
Subject(s) - handwriting , suspect , computer science , multivariate statistics , probabilistic logic , set (abstract data type) , character (mathematics) , value (mathematics) , statistics , artificial intelligence , natural language processing , mathematics , speech recognition , psychology , machine learning , geometry , criminology , programming language
Summary. The evaluation of handwritten characters that are selected from an anonymous letter and written material from a suspect is an open problem in forensic science. The individualization of handwriting is largely dependent on examiners who evaluate the characteristics in a qualitative and subjective way. Precise individual characterization of the shape of handwritten characters is possible through Fourier analysis: each handwritten character can be described through a set of variables such as the surface and harmonics as demonstrated by Marquis and co‐workers in 2005. The assessment of the value of the evidence is performed through the derivation of a likelihood ratio for multivariate data. The methodology allows the forensic scientist to take into account the correlation between variables, and the non‐constant variability within sources (i.e. individuals). Numerical procedures are implemented to handle the complexity and to compute the marginal likelihood under competing propositions.