Description of original award (Fiscal Year 2015, $217,450)
As submitted by the proposer: The proposed work includes critical next steps for transferring a low-cost, fast, and accurate next generation system for toolmark analysis into the forensic lab. In 2013, we began development of a 3D surface topography imaging and analysis system for firearm forensics based on the GelSight imaging technology and feature-based image comparison algorithms. To date, we developed prototype software and hardware, conducted a series of deployment studies with local and state forensic labs, completed matching experiments on a large dataset of over 600 casings from over 250 different 9mm Luger firearms, developed aperture shear profile extraction algorithms, devised matching algorithms for breech-face impressions and aperture shears, developed a 0/1 confidence score, and evaluated cross-modality matching (i.e., the matching of a GelSight scan with a confocal scan). This year (2015) we are focusing on developing scanning performance metrics, establishing best scanning practices, assessing scanner performance, conducting an inter-operator validation study, and establishing a quality control process. The technology shows excellent (and improving) match accuracy and we are excited to transition the methodology more closely into the crime lab.
Building from our recent success in the scanning and analysis of breech-face impressions and aperture shears, the proposed work (2016) takes important next steps towards moving the developed technology into the crime lab. Across three aims, the proposed work extends the imaging and analysis methods to include firing pin impressions, develops and evaluates a blind verification tool, and researches the feasibility of virtual microscopy. Through all aims we will work with our forensic and academic collaborators and continue deployment studies with several sites.
These goals represent a series of R&D steps towards the creation and validation of a novel technology platform for comparing 3D surface topographies for firearm forensics. The assembled project team and committed colleagues include PhD-level computer scientists, forensic firearms examiners, and metrology experts each strongly committed to getting the research right and advancing the field. Overall, this work will develop analytic techniques, grounded in mathematical science and able to provide accurate quantitative sample comparison and database search. This should benefit law enforcement and their ability to present forensic evidence in the courtroom.
This project contains a research and/or development component, as defined in applicable law.
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