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Optimization of a Statistical Algorithm for Objective Comparison of Toolmarks
Abstract
Due to historical legal challenges, there is a driving force for the development of objective methods of forensic toolmark identification. This study utilizes an algorithm to separate matching and nonmatching shear cut toolmarks created using fifty sequentially manufactured pliers. Unlike previously analyzed striated screwdriver marks, shear cut marks contain discontinuous groups of striations, posing a more difficult test of algorithm applicability. The algorithm compares correlation between optical 3D toolmark topography data, producing a Wilcoxon rank sum test statistic. Relative magnitude of this metric separates the matching and nonmatching toolmarks. Results show a high degree of statistical separation between matching and nonmatching distributions. Further separation is achieved with optimized input parameters and implementation of a “leash” preventing a previous source of outliers—however complete statistical separation was not achieved. This paper represents further development of objective methods of toolmark identification and further validation of the assumption that toolmarks are identifiably unique.
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Research works printed but not linked: 10
- Faden D, 2007, Statistical confirmation of empirical observations concerning toolmark striae, AFTE J, 39, 205
- 10.1111/j.1556-4029.2010.01424.x · DOI
- 10.1111/j.1556-4029.2009.01221.x · DOI
- Cassidy FH, 1980, Examination of toolmarks from sequentially manufactured tongue‐and‐groove pliers, J Forensic Sci, 25, 796, 10.1520/JFS11294J · DOI
- 10.2172/1082976 · DOI
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- AFTE, 2007, Glossary of the association of firearm and toolmark examiners
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Garrett, B. L. (2020) · Annual Review of Criminology · doi:10.1146/annurev-criminol-011518-024739 · Cited by 35
Metadata
- Authors
- Spotts, R., Chumbley, L. S., Ekstrand, L., Zhang, S., & Kreiser, J.
- Affiliations
- Iowa State University (US)
- Illinois State Police Retired, 3112 Sequoia Dr. Springfield IL 62712
- Corresponding author
- Spotts, Ryan
- ORCID
- Zhang, Song
- Venue
- Journal of Forensic Sciences
- Publisher
- Wiley
- Published
- 2014-11-25
- Volume
- 60
- Issue
- 2
- Pages
- 303-314
- ISSN
- 0022-1198 (ISSN-L)
- 1556-4029
- OpenAlex
- W2169457609
- Cited by
- 17
- References
- 0
- Citations by year
- 2024: 4 · 2021: 2 · 2019: 2 · 2018: 1 · 2017: 3 · 2016: 3 · 2015: 1 · 2014: 1
- FWCI
- 2.39
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Forensic Sciences (publishedVersion)
- PubMed (publishedVersion)
- Iowa State University Digital Repository (Iowa State University) (submittedVersion)
- Funders
- National Institute of Justice (2009-DNR-119)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Processing and 3D Reconstruction
- Health Sciences › Medicine › Pathology and Forensic Medicine › Forensic Fingerprint Detection Methods
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Keywords
- pliers, correlation analysis, Mann-Whitney test, algorithm parameter optimization, outlier removal
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- Spotts, R., Chumbley, L. S., Ekstrand, L., Zhang, S., & Kreiser, J. (2015). Optimization of a Statistical Algorithm for Objective Comparison of Toolmarks. Journal of Forensic Sciences. https://doi.org/10.1111/1556-4029.12642
