@article{hadler,
author = {Hadler, Jeremy R. and Morris, Max D.},
title = {An Improved Version of a Tool Mark Comparison Algorithm},
journal = {Journal of Forensic Sciences},
volume = {63},
number = {3},
pages = {849-855},
keywords = {forensic science, striae, profilometry, U-statistic, correlated data, screwdriver},
doi = {10.1111/1556-4029.13640},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1556-4029.13640},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/1556-4029.13640},
abstract = {Abstract Chumbley et al. (2010) described a statistically based algorithm for comparing pairs of tool marks. They presented empirical evidence that the algorithm produces well-separated similarity score values for “matching” and “non-matching” pairs of tool marks. However, the algorithm has two substantial weaknesses. First, it is “uncalibrated” in the sense that error rates can be determined only through empirical investigation. Second, it relies on a randomized test and can lead to different similarity scores when the algorithm is repeatedly applied to the same pair of tool marks. We present an improved version of the procedure, which eliminates the randomized scores and yields more consistent and predictable error rate control. This is accomplished by replacement of a random sampling step from the original algorithm with a deterministic process. We demonstrate the improved algorithm and compare its performance to the original by applying to known “matching” and “non-matching” pairs of tool marks.},
year = {2018}
}


@article{gkhh-chumbley,
author = {Krishnan, Ganesh and Hofmann, Heike},
title = {Adapting the Chumbley Score to Match Striae on Land Engraved Areas (LEAs) of Bullets,},
journal = {Journal of Forensic Sciences},
volume = {64},
number = {3},
pages = {728-740},
keywords = {forensic science, toolmark, cross-correlation, Mann–Whitney U statistic, land engraved areas, algorithm, signatures, same-source problem},
doi = {10.1111/1556-4029.13950},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1556-4029.13950},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/1556-4029.13950},
abstract = {Abstract The same-source problem remains a major challenge in forensic toolmark and firearm examination. Here, we investigate the applicability of the Chumbley method (J Forensic Sci, 2018, 63, 849; J Forensic Sci, 2010, 55, 953) (10,12), developed for screwdriver markings, for same-source identification of striations on bullet LEAs. The Hamby datasets 44 and 252 measured by NIST and CSAFE (high-resolution scans) are used here. We provide methods to identify parameters that minimize error rates for matching of LEAs, and a remedial algorithm to alleviate the problem of failed tests, while increasing the power of the test and reducing error rates. For 85,491 land-to-land comparisons (84,235 known nonmatches and 1256 known matches), the adapted test does not provide a result in 176 situations (originally more than 500). The Type I and Type II error rates are 7.2\% (6105 out of 84,235) and 21.4\% (271 out of 1256), respectively. This puts the proposed method on similar footing as other single-feature matching approaches in the literature.},
year = {2019}
}


@phdthesis{hadlermorristhesis,
	title = {Forensic tool mark comparisons: {Tests} for the null hypothesis of different sources},
	language = {en},
	school = {Iowa State University},
	author = {Hadler, Jeremy R},
	year = {2017},
	file = {viewcontent.pdf:C\:\\Users\\thinkpad-bond\\Zotero\\storage\\92HGINRM\\viewcontent.pdf:application/pdf}
}

@article{bachrach,
	title = {A {Statistical} {Validation} of the {Individuality} and {Repeatability} of {Striated} {Tool} {Marks}: {Screwdrivers} and {Tongue} and {Groove} {Pliers}*},
	volume = {55},
	copyright = {© 2010 Intelligent Automation, Inc. Journal compilation © 2010 American Academy of Forensic Sciences},
	issn = {1556-4029},
	shorttitle = {A {Statistical} {Validation} of the {Individuality} and {Repeatability} of {Striated} {Tool} {Marks}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1556-4029.2009.01221.x},
	doi = {10.1111/j.1556-4029.2009.01221.x},
	abstract = {Abstract: Tool mark identification relies on the premise that microscopic imperfections on a tool’s working surface are sufficiently unique and faithfully transferred to enable a one-to-one association between a tool and the tool marks it creates. This paper presents a study undertaken to assess the validity of this premise. As part of this study sets of striated tool marks were created under different conditions and on different media. The topography of these tool marks was acquired and the degree of similarity between them was quantified using well-defined metrics. An analysis of the resulting matching and nonmatching similarity distributions shows nearly error-free identification under most conditions. These results provide substantial support for the validity of the premise of tool mark identification. Because the approach taken in this study relies on a quantifiable similarity metric, the results have greater repeatability and objectivity than those obtained using less precise measures of similarity.},
	language = {en},
	number = {2},
	urldate = {2019-04-17},
	journal = {Journal of Forensic Sciences},
	author = {Bachrach, Benjamin and Jain, Anurag and Jung, Sung and Koons, Robert D.},
	year = {2010},
	keywords = {3D imaging, automated comparison of microscopic tool mark evidence, forensic science, screwdrivers, statistical methodology, striations, tongue and groove pliers, tool mark identification},
	pages = {348--357},
	file = {Snapshot:C\:\\Users\\thinkpad-bond\\Zotero\\storage\\RHH9N94Q\\j.1556-4029.2009.01221.html:text/html}
}
