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Publication Citation: Striation Density for Predicting the Identifiability of Fired Bullets

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Author(s): Wei Chu; Jun-Feng Song; Theodore V. Vorburger; Susan M. Ballou;
Title: Striation Density for Predicting the Identifiability of Fired Bullets
Published: September 01, 2010
Abstract: Without a selection procedure to exclude the bullets having insufficient individualized ballistics signature, automated ballistics identification systems will correlate an evidence bullet with all reference bullets stored in the database. Correlations that include such bullets with ballistics signature of poor quality increase the workload and may affect the correlation accuracy. In this paper, a parameter called striation density, ds, is proposed for determining bullet identifiability. After the image preprocessing, an edge detection technique is used to extract the feature edges. Then a filtering process is performed to remove all edge elements irrelevant to the striation marks. The resulting binary image distinctly reflects the amount and distribution of striation marks on the imaged bullet land. Then striation density is calculated for determining the quality of images and judging their identifiability. This function can provide ballistics identification systems with a quantitative criterion to estimate and predict the reliability of ballistics identifications.
Citation: Journal of Forensic Sciences
Volume: 55
Issue: 5
Pages: pp. 1222 - 1226
Keywords: forensic science; ballistics identification; striation density; edge detection; morphology
Research Areas: Homeland Security/Forensics/Human Identity