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Application of Machine Learning to Toolmarks: Statistically Based Methods for Impression Pattern Comparisons

Award Information

Award #
2009-DN-BX-K041
Funding Category
Competitive
Location
Congressional District
Status
Closed
Funding First Awarded
2009
Total funding (to date)
$704,189

Description of original award (Fiscal Year 2009, $704,189)

The authors propose to develop standardized methodologies to study and critically evaluate impression evidence. Three-dimensional vector data of the cartridge case impressions will be collected using high resolution 3D laser scanning and stored in a large database. This will generate a digital 3-dimensional map of the impression surface using X, Y, and Z coordinates. The data will then be examined with multiple multivariate statistical methods in order to quantify the criteria necessary to match a physical marking.

ca/ncf

Date Created: September 22, 2009