NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.
Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.
An official website of the United States government
Here’s how you know
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.
Chu, W.
, Song, J.
, Vorburger, T.
and Ballou, S.
(2010),
Striation Density for Predicting the Identifiability of Fired Bullets, Journal of Forensic Sciences
(Accessed October 11, 2025)