Fired bullet signature correlation using the Congruent Matching Profile Segments (CMPS) method
•Summarize the characteristics of striated tool mark identification algorithms.•Address the challenges of varying lateral scales and poorly marked sections.•Correlate the striation profile in segments based on the discretization principle.•Use multiple correlation peak inspection and multi-scale cor...
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Veröffentlicht in: | Forensic science international 2019-12, Vol.305, p.109964-109964, Article 109964 |
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Sprache: | eng |
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Zusammenfassung: | •Summarize the characteristics of striated tool mark identification algorithms.•Address the challenges of varying lateral scales and poorly marked sections.•Correlate the striation profile in segments based on the discretization principle.•Use multiple correlation peak inspection and multi-scale correlation in segments.•New algorithm achieved a better separation compared to profile-based algorithm.
We introduce the Congruent Matching Profile Segments (CMPS) method for objective comparison of striated tool marks and apply it to bullet signature correlations. The method is derived from the congruent matching cell (CMC) method developed for the comparison of impressed tool marks. The proposed method is designed to increase comparison accuracy by addressing the comparison challenges caused by striae profiles with different lateral scales, varying vertical (height) scales, and sections that are poorly marked or have little to no similarity. Instead of correlating the entire profiles extracted from striated tool marks, the method divides one of the compared profiles into segments. Each segment is then correlated with the other profile. The CMPS method uses the normalized cross-correlation function with multiple correlation peak inspection to determine the number of profile segments that have both significant topography similarity and a congruent registration position. Initial tests were performed on the land engraved areas (LEAs) of 35 bullets fired from 10 consecutively manufactured pistol barrels. The results show clear separation between the CMPS scores of the 549 known non-matching (KNM) LEA profiles and the 46 known matching (KM) LEA profiles. These results are an improvement over those obtained using the correlation coefficient score of whole profiles. The large number of CMPS segment correlations may facilitate a statistical approach to error rate estimations. |
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ISSN: | 0379-0738 1872-6283 |
DOI: | 10.1016/j.forsciint.2019.109964 |