Forensic surface metrology: tool mark evidence.
Carol Gambino1, Patrick McLaughlin, Loretta Kuo
1Department of Sciences, John Jay College of Criminal Justice, City University of New York, New York, USA.
Scanning
|June 29, 2011
Summary
Forensic tool mark analysis can now be objectively corroborated. This study developed a new system using confocal microscopy, principal component analysis, and support vector machines to reduce subjectivity and provide confidence levels for evidence identification.
Area of Science:
- Forensic Science
- Materials Science
- Computer Science
Background:
- Impression evidence analysis in forensics often relies on subjective comparisons, leading to courtroom scrutiny.
- A lack of universally accepted systems for generating objective, numerical data to support visual comparisons in tool mark analysis exists.
- This research addresses the need for objective methods in firearm and tool mark examination.
Purpose of the Study:
- To develop a methodology for the objective evaluation and association of striated tool marks with their generating tools.
- To introduce a system that generates numerical data to corroborate subjective visual comparisons in forensic tool mark analysis.
- To establish confidence levels for tool mark identifications using conformal prediction theory.
Main Methods:
- High-resolution white light confocal microscopy was used to collect 3D surface topographies of 58 primer shear marks from Glock 19 pistols.
- Waviness profiles were extracted from the 3D surface data and processed using principal component analysis (PCA) for dimension reduction.
- Support vector machines (SVM) were employed for profile-gun associations, with conformal prediction theory (CPT) used to establish confidence levels.
Main Results:
- The combined PCA-SVM and CPT approach achieved an empirical error rate of 3.5% at the 95% confidence level.
- Bootstrap-based computations indicated an estimated error rate of 0%, suggesting a low error rate for larger datasets.
- The methodology successfully provided objective, quantifiable data to support the association of tool marks with specific firearms.
Conclusions:
- The developed methodology offers an objective approach to tool mark analysis, reducing reliance on subjective comparisons.
- Conformal prediction theory provides a robust framework for assigning confidence levels to algorithmic identifications in forensic science.
- This system has practical implications for courtroom application, enhancing the reliability and admissibility of tool mark evidence.
