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Handwriting Evidence Evaluation Based on the Shape of Characters: Application of Multivariate Likelihood Ratios * ,†
Author(s) -
Marquis Raymond,
Bozza Silvia,
Schmittbuhl Matthieu,
Taroni Franco
Publication year - 2011
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/j.1556-4029.2010.01602.x
Subject(s) - handwriting , multivariate statistics , computer science , suspect , bayesian probability , multivariate analysis , natural language processing , artificial intelligence , statistics , pattern recognition (psychology) , speech recognition , psychology , mathematics , machine learning , criminology
A novel Bayesian methodology has been developed to quantitatively assess handwriting evidence by means of a likelihood ratio (LR) designed for multivariate data. This methodology is presented and its applicability is shown through a simulated case of a threatening anonymous text where a suspect is apprehended. The shape of handwritten characters a , d , o, and q of the threatening text was compared with characters of the true writer, and then with two other writers, one with similar and one with dissimilar characters shape compared to the true writer. In each of these three situations, 100 draws of characters were made and the resulting distributions of LR were established to consider the natural handwriting variation. LR values supported the correct hypothesis in every case. This original Bayesian methodology provides a coherent and rigorous tool for the assessment of handwriting evidence, contributing undoubtedly to integrate the field of handwriting examination into science.