Abstract
A study is described that involves enhancing the scientific underpinnings of forensic handwriting analysis. Forensic document examiners are individuals who carefully scrutinize handwriting samples in a variety of civil and criminal cases and attest to the originators of handwritten documents (wills, ransom notes, letters found at crime scenes, literature drafts and so forth). A large-scale study is described that addresses the concerns of the US National Academy of Sciences regarding handwriting analyses. An original contribution of our work is the creation of a comprehensive list of handwriting attributes (developed by T. Vastrick) which served as the reference for our attribute agreement analysis. An initial list of over 2,500 potential attributes was reduced to 896 features which were free of disagreements among the examiners across multiple specimens. Challenges in collecting handwritten samples from the target population are described and a methodology to address these issues is developed. Challenges in the analyses and future directions are identified.
Keywords
- Data Collection Process
- Stratification Variable
- National Research Council Report
- Attribute Agreement
- Data Collection Plan
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Acknowledgements
This work was supported by a National Institute of Justice grant through the National Center for Forensic Science at the University of Central Florida.
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Boulanger, M., Johnson, M.E., Vastrick, T.W. (2014). Development of an Extensive Forensic Handwriting Database: Statistical Components. In: Melas, V., Mignani, S., Monari, P., Salmaso, L. (eds) Topics in Statistical Simulation. Springer Proceedings in Mathematics & Statistics, vol 114. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2104-1_8
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DOI: https://doi.org/10.1007/978-1-4939-2104-1_8
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