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Title: Statistical methods for the forensic analysis of striated tool marks

Thesis/Dissertation ·
DOI:https://doi.org/10.2172/1226173· OSTI ID:1226173
 [1]
  1. Iowa State Univ., Ames, IA (United States)

In forensics, fingerprints can be used to uniquely identify suspects in a crime. Similarly, a tool mark left at a crime scene can be used to identify the tool that was used. However, the current practice of identifying matching tool marks involves visual inspection of marks by forensic experts which can be a very subjective process. As a result, declared matches are often successfully challenged in court, so law enforcement agencies are particularly interested in encouraging research in more objective approaches. Our analysis is based on comparisons of profilometry data, essentially depth contours of a tool mark surface taken along a linear path. In current practice, for stronger support of a match or non-match, multiple marks are made in the lab under the same conditions by the suspect tool. We propose the use of a likelihood ratio test to analyze the difference between a sample of comparisons of lab tool marks to a field tool mark, against a sample of comparisons of two lab tool marks. Chumbley et al. (2010) point out that the angle of incidence between the tool and the marked surface can have a substantial impact on the tool mark and on the effectiveness of both manual and algorithmic matching procedures. To better address this problem, we describe how the analysis can be enhanced to model the effect of tool angle and allow for angle estimation for a tool mark left at a crime scene. With sufficient development, such methods may lead to more defensible forensic analyses.

Research Organization:
Ames Lab., Ames, IA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC02-07CH11358
OSTI ID:
1226173
Report Number(s):
IS-T 3087
Country of Publication:
United States
Language:
English