Several recent studies have called for improved imaging technology and matching algorithms to support firearm identification. The author investigated and developed a novel, accurate, and low-cost system for structural 3D imaging and comparison of cartridge cases.

He was able to demonstrate the system’s potential for increasing the quality and reducing the cost of forensic analyses. The project, named Top-Match, combines the recently developed GelSight high-resolution surface topography imaging system with state-of-the-art algorithms for matching structural features.

Compared to competing technologies, the author’s GelSight-based system is fast, inexpensive, and not sensitive to the optical properties of the material being measured. The project aimed to extend the system to measure and compare striated toolmarks (e.g., aperture shear), to integrate these marks into the scoring function, and to investigate matching algorithms for comparing 3D surface topographies captured using different imaging modalities (e.g., GelSight vs. confocal microscopy).

The author developed a robust algorithm for extracting the linear profile of aperture shears. This method is able to extract profiles from curved, flat, or arced shears. Manual examination of the extracted profiles shows informative profiles can be extracted for approximately 88 percent of Glock casings.

These linear profiles can then be matched as part of a matching algorithm, which demonstrates a significant improvement in Glock matching ability when the shears are considered.

The author created an open file format (X3P) for the free exchange of 3D surface topography data. This format allowed collaboration with his colleagues at National Institute of Standards and Technology (NIST). They demonstrated that cross-modality matching is possible and that, in many cases, it works extremely well.

To achieve these results, the confocal scans required simple preprocessing (mainly interpolation of drop-outs and denoising with a low-pass filter). The system is able to accurately identify known matches when scans were acquired with GelSight or Confocal scanning systems. The algorithm was also able to identify known matches where one scan is a GelSight scan and the other is a Confocal scan.

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