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Developing a Database of Cursive and Printed Handwriting Characteristics

NCJ Number
251407
Date Published
November 2017
Length
2 pages
Annotation

This project, which was funded by the U.S. Justice Department's National Institute of Justice (NIJ), conducted a statistical study of handwriting characteristics (both cursive and printed) for the purpose of developing a database that strengthens the bases of handwriting comparisons.

Abstract

Overall, the project developed statistically valid frequency occurrence proportions of handwriting and hand-printing characteristics based on samples from throughout the United States. Two forensic document examiners, a statistician, and a statistical-standards expert analyzed 1,719 handwriting specimens (880 cursive and 839 hand-printed specimens) in developing an objective database of characteristics that closely reflects the demographic proportions of the United States. The researchers note that this project is a statistical study, not a forensic study. The database developed can be part of an examiner's "estimation of confidence" when making handwriting comparisons in courtroom testimony. The researchers report that the analysis of the specimens yielded numerous specific frequency occurrence proportions, and additional analyses showed quantitatively the extent to which demographic features such as age, gender, ethnicity, education, locations of second/third grade training, and handedness impact the presence/absence of features. The researchers examined hundreds of handwriting characteristics, including enclosed loops, direction of strokes, up and down strokes, connections between letters, and the comparative height of letter peaks. Just over 900 handwriting characteristics were included in the analysis. The researchers conclude, however, that although the database they created provides a baseline figure of distinctiveness for any cursive or hand-printed entry, this project has "just scratched the surface of the detail that is reviewed and is designed to give the user an appreciation of the probabilistic level of individuality in handwriting."

Date Published: November 1, 2017