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Pilot Study of Automated Bullet Signature Identification Based on Topography Measurements and Correlations * †
Author(s) -
Chu Wei,
Song John,
Vorburger Theodore,
Yen James,
Ballou Susan,
Bachrach Benjamin
Publication year - 2010
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/j.1556-4029.2009.01276.x
Subject(s) - signature (topology) , ranking (information retrieval) , correlation , barrel (horology) , identification (biology) , cross correlation , computer science , artificial intelligence , pattern recognition (psychology) , mathematics , statistics , engineering , mechanical engineering , botany , geometry , biology
A procedure for automated bullet signature identification is described based on topography measurements using confocal microscopy and correlation calculation. Automated search and retrieval systems are widely used for comparison of firearms evidence. In this study, 48 bullets fired from six different barrel manufacturers are classified into different groups based on the width class characteristic for each land engraved area of the bullets. Then the cross‐correlation function is applied both for automatic selection of the effective correlation area, and for the extraction of a 2D bullet profile signature. Based on the cross‐correlation maximum values, a list of top ranking candidates against a ballistics signature database of bullets fired from the same model firearm is developed. The correlation results show a 9.3% higher accuracy rate compared with a currently used commercial system based on optical reflection. This suggests that correlation results can be improved using the sequence of methods described here.