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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.
Chu et al. (Tue,) studied this question.