Pilot study on deformed bullet correlation

•Summarize the deformation types of bullet land engraved area (LEA) striations.•Propose a profile reconstruction process to straighten distorted LEAs.•Use CMPS method for an objective comparison with varying lateral scale factors. Most studies on bullet identification address test fired bullets that have near pristine striated marks on the land engraved areas (LEAs). However, in case work, bullets found at a crime scene may be severely deformed or fragmented. The resulting missing, expanded, or distorted LEA striations can cause challenges in toolmark comparisons performed by examiners or algorithms. In this paper, an image reconstruction procedure is proposed that, in combination with the Congruent Matching Profile Segments (CMPS) profile comparison method, facilitates the algorithmic correlation of deformed bullets. Initial validation tests were conducted using 57 bullets, with varying degrees of fragmentation or deformation, that were fired from the same 9mm Luger caliber Luger pistol. The bullets spanned 7 different ammunition brands. The CMPS method was applied to correlate the LEA striation profiles extracted from LEA topography images that were corrected for pattern distortion. 15 bullet LEAs, out of 250 bullet LEAs that could be measured, had major distortions. Two sets of comparison tests were conducted, corresponding to a same source and specific source scenario: 1) comparison of the severely distorted LEAs with a near-pristine reference bullet, before and after image reconstruction, and 2) inter comparisons of distorted LEAs, before and after reconstruction. The reconstruction process significantly improved the correlation results when dealing with distorted bullet LEAs. In general, the improvement was larger for samples with relatively large deformation and good striation visibility. Samples with approximately parallel striations tend to have less improvement of CMPS results after profile reconstruction since the CMPS method itself can correct certain scale errors.