Classifying handwriting samples according to their type using discriminant analysis
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RIS BIB ENDNOTEClassifying handwriting samples according to their type using discriminant analysis
Data publikacji: 08.05.2023
Problems of Forensic Sciences (Z Zagadnień Nauk Sądowych), 2022, 132, s. 241 - 257
https://doi.org/10.4467/12307483PFS.22.013.17686Autorzy
Classifying handwriting samples according to their type using discriminant analysis
Classifying handwriting samples according to their type (i.e. natural, disguised, traced, simulated or unintentionally unnatural) is an important task in handwriting analysis. It may facilitate the collection of writing standards and also help experts to assess the differences between questioned material and comparative samples or to choose the best writing features and the most relevant examination protocol for the case. Current research aimed to create a method for classifying the type of a handwriting sample using discriminant analysis. Five basic types (i.e. natural, disguised, traced, simulated and unintentionally unnatural) and some subtypes were included in this study. Participants (N = 139) wrote their full signatures, fictional signatures or a short sentence. Motor and dimensional features were assessed. The methods proved to be more than twice as accurate in classifying samples according to their type than a random choice probability (e.g. 44% as opposed to 17% for the 6-types classifier). This proof-of-a-concept study demonstrates that handwriting samples may be classified according to their type with satisfying accuracy based on their writing features and statistical tools of discriminant analysis. However, further studies are necessary to improve the accuracy of the method.
1. Alford, E. F. (1970). Disguised handwriting. A statistical survey of how handwriting is most frequently disguised. Journal of Forensic Sciences, 15, 476–488.
2. Bird, C., Found, B., Ballantyne, K., Rogers, D. (2010). Forensic handwriting examiners’ opinions on the process of production of disguised and simulated signatures. Forensic Science International, 195, 103–107.
3. Durina, M. E. (2005). Disguised signatures: random or repetitious? Journal of the American Society of Questioned Document Examiners, 8, 9–16.
4. Ellen, D., Day, S., Davies, C. (2018). The scientific examination of documents. Methods and techniques (4th ed., p. 248). Boca Raton, Florida: CRC Press.
5. Harris, J. J. (1953). Disguised handwriting. Journal of Criminal Law, Criminology & Police Science, 43, 5, 685–689.
6. Huber, R. A., Headrick, A. M. (1999). Handwriting identification: Facts and fundamentals (p. 434). Boca Raton, Florida: CRC Press.
7. Koppenhaver, K. M. (2007). Forensic document examination: Principles and practice (p. 307). Totowa, New York: Humana Press Inc.
8. Leung, S. C., Cheng, Y. S., Fung, H. T, Poon, N. L. (1993). Forgery I – simulation. Journal of Forensic Sciences, 38, 402–412.
9. Matuszewski, S. (2011). Types of handwriting samples. Problems of Forensic Sciences, 87, 181–192.
10. Muehlberger, J. (1990). Identifying simulations: practical considerations. Journal of Forensic Sciences, 35, 368–374.
11. Wendt, G. W. (2003). Statistical observations of disguised signatures. Journal of the American Society of Questioned Document Examiners, 3, 19–27.
Informacje: Problems of Forensic Sciences (Z Zagadnień Nauk Sądowych), 2022, 132, s. 241 - 257
Typ artykułu: Oryginalny artykuł naukowy
Tytuły:
Classifying handwriting samples according to their type using discriminant analysis
Classifying handwriting samples according to their type using discriminant analysis
Uniwersytet Adama Mickiewicza w Poznaniu, Wieniawskiego 1, 61-712 Poznań
Publikacja: 08.05.2023
Otrzymano: 27.12.2022
Zaakceptowano: 31.01.2023
Status artykułu: Otwarte
Licencja: CC BY-NC-ND
Udział procentowy autorów:
Korekty artykułu:
-Języki publikacji:
Angielski, PolskiLiczba wyświetleń: 339
Liczba pobrań: 301
Sugerowane cytowania: Vancouver