Objective Identification of Bullets Based on 3D Pattern Matching and Line Counting Scores
by Danny Roberge, Alain Beauchamp and Serge Levesque
The emergence of technology enabling the capture of surface topographies down to submicron depth resolution has been the catalyst for the field of computerized objective firearm identification of fired bullets and cartridge cases.
Objectivity is achieved through the statistical analysis of various scores of known matches and known nonmatches in an exhibit pair comparison. This requires the capture of large quantities of bullet or cartridge case topographies. The main goal of this study was to develop an objective identification method for bullets fired from conventionally-rifled barrels, and to test this method on public and proprietary 3D bullet image datasets captured at two lateral resolutions.
Two newly developed bullet identification scores, the Line Counting Score and the Pattern Matching Score, computed on 3D topographies yielded perfect match versus nonmatch separation for three different sets used in the standard Hamby-Brundage Test. A similar analysis performed using a larger, more-realistic set, allowed us to define a discriminative line at a false match rate of 1/10000 on a 2D plot that shows both identification scores for matches and nonmatches.