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Applied Research and Development of a Three-dimensional Topography System for Imaging and Analysis of Striated and Impressed Tool Marks for Firearm Identification using GelSight

Award Information

Award #
2013-R2-CX-K005
Funding Category
Competitive
Location
Congressional District
Status
Closed
Funding First Awarded
2013
Total funding (to date)
$193,000

Description of original award (Fiscal Year 2013, $193,000)

The proposed work will investigate and develop a novel, accurate, and low-cost system for structural 3D imaging and comparison of cartridge cases and will demonstrate the system's potential for increasing the quality and reducing the cost of forensic analyses. The proposal directly addresses several aims of the NIJ's Applied Research and Development in Forensic Science for Criminal Justice Purposes program: it increases the quality and efficiency of forensic analysis, it develops new instrumentation systems, and it provides a novel approach to enhancing the analysis and interpretation of forensic data derived from physical evidence. Several recent studies have called for improved imaging technology and matching algorithms to support firearm identification. The proposed project combines the recently developed GelSight high-resolution surface topography imaging system with state-of-the-art algorithms for matching image features. Compared to competing technologies, our GelSight based system is fast, inexpensive, and not sensitive to the optical properties of the material being measured. There are three aims to the proposal. Aim 1 involves algorithm development and testing for imaging striated tool marks with a focus on primer shears. Aim 2 develops a statistical model that integrates the primer shear similarity measure from Aim 1 with our current breech-face impression similarity measure. This will create a more accurate measure of similarity than either score in isolation. Finally, the research pursued in Aim 3 will develop matching algorithms for comparing 3D surface topographies captured using different imaging modalities (e.g., GelSight vs. confocal microscopy). Two completed feasibility studies described in this proposal, support the presented aims. The studies demonstrate the ability to extract and compare striated tool marks from GelSight measured surface topographies and provide strong support for the feasibility of cross-modal matching. The proposal will be completed by Cadre Research Labs, a scientific computing contract research organization, working in collaboration with GelSight Inc, a company formed by the MIT researchers who developed the GelSight surface topography imaging technology. The two companies will collaborate closely with Todd Weller, a firearms identification specialist and Criminalist in the Oakland Police Department. Todd has over 13 years of forensic experience and graduated from the National Firearms Examiner Academy (NFEA). The proposal also describes collaborative work with colleagues at NIST and the International Forensic Science Laboratory & Training Centre in Indianapolis. The proposed research will make use of a large set of new and previously collected test fires and will be evaluated both internally and at external locations (including the Oakland Police Department, the Contra Costa Office of the Sheriff Crime Lab, and the ATF). Overall, this work will develop analytic techniques, grounded in mathematical science and able to provide accurate quantitative sample comparison and database search. This will benefit law enforcement and their ability to present firearm identification and tool mark evidence in the courtroom. Upon completion of the proposed project we will have created the first deployable version of the GelSight based imaging system capable of analyzing both impressed and striated tool marks. Interim reports will be provided as required by the NIJ. A final report will summarize the completion and results of the four aims. In future work, the proposed framework can be extended to a range of other tool mark comparisons (e.g., bullet LEA and the firing pin impression). ca/ncf
Date Created: September 8, 2013