Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Striation Density for Predicting the Identifiability of Fired Bullets

Published

Author(s)

Wei Chu, Jun-Feng Song, Theodore V. Vorburger, Susan M. Ballou

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

Keywords

forensic science, ballistics identification, striation density, edge detection, morphology

Citation

Chu, W. , Song, J. , Vorburger, T. and Ballou, S. (2010), Striation Density for Predicting the Identifiability of Fired Bullets, Journal of Forensic Sciences (Accessed November 9, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created August 31, 2010, Updated February 19, 2017