Elucidating the relationships between two automated handwriting feature quantification systems for multiple pairwise comparisons

Recent advances in complex automated handwriting identification systems have led to a lack of understandability of these systems’ computational processes and features by the forensic handwriting examiners that they are designed to support. To mitigate this issue, this research studied the relationsh...

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Vydáno v:Journal of forensic sciences Ročník 67; číslo 2; s. 642 - 650
Hlavní autoři: Fuglsby, Cami, Saunders, Christopher, Ommen, Danica M., Buscaglia, JoAnn, Caligiuri, Michael P.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Wiley Subscription Services, Inc 01.03.2022
Témata:
Algorithms
automated handwriting system
Automation
Biometrics
black box system
Discrimination
Examiners
Forensic sciences
Handwriting
Handwriting analysis
Kinematics
Measurement
questioned documents
Scholarship
Statistical methods
statistical modeling
validity
white box system
white box system
black box system
handwriting
statistical modeling
validity
questioned documents
automated handwriting system
ISSN:0022-1198, 1556-4029, 1556-4029
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Popis
Shrnutí:Recent advances in complex automated handwriting identification systems have led to a lack of understandability of these systems’ computational processes and features by the forensic handwriting examiners that they are designed to support. To mitigate this issue, this research studied the relationship between two systems: FLASH ID®, an automated handwriting/black box system that uses measurements extracted from a static image of handwriting, and MovAlyzeR®, a system that captures kinematic features from pen strokes. For this study, 33 writers each wrote 60 phrases from the London Letter using cursive writing and handprinting, which led to thousands of sample pairs for analysis. The dissimilarities between pairs of samples were calculated using two score functions (one for each system). The observed results indicate that dissimilarity scores based on kinematic spatial‐geometric pen stroke features (e.g., amplitude and slant) have a statistically significant relationship with dissimilarity scores obtained using static, graph‐based features used by the FLASH ID® system. Similar relationships were observed for temporal features (e.g., duration and velocity) but not pen pressure, and for both handprinting and cursive samples. These results strongly imply that both the current implementation of FLASH ID® and MovAlyzeR® rely on similar features sets when measuring differences in pairs of handwritten samples. These results suggest that studies of biometric discrimination using MovAlyzeR®, specifically those based on the spatial‐geometric feature set, support the validity of biometric matching algorithms based on FLASH ID® output.
Bibliografie:Funding information
This research was supported by the National Institute of Justice, 2017‐DN‐BX‐0148. Cami Fuglsby received additional support from the National Science Foundation, DGE‐1828492.
The preliminary findings were presented at the 71st Annual Scientific Meeting of the American Society of Questioned Document Examiners, August 4–8, 2019, in Cary, NC, and at the 72nd Annual Scientific Meeting of the American Academy of Forensic Sciences, February 17–22, 2020, in Anaheim, CA. Statistical aspects of this research were presented at the 2021 Joint Statistical Meetings, August 8–12, 2021, held virtually.
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ISSN:0022-1198
1556-4029
1556-4029
DOI:10.1111/1556-4029.14914