@article{ref1,
title="A multimodal fusion approach for bullet identification systems",
journal="Journal of forensic sciences",
year="2019",
author="Bigdeli, Saeed and Ebrahimi Moghaddam, Mohsen",
volume="64",
number="3",
pages="741-753",
abstract="In the field of forensic science, bullet identification is based on the fact that firing the cartridge from a barrel leaves exclusive microscopic striation on the fired bullets as the fingerprint of the firearm. The bullet identification methods are categorized in 2-D and 3-D based on their image acquisition techniques. In this study, we focus on 2-D optical images using a multimodal technique and propose several distinct methods as its modalities. The proposed method uses a multimodal rule-based linear weighted fusion approach which combines the semantic level decisions from different modalities with a linear technique that its optimized modalities weights have been identified by the genetic algorithm. The proposed approach was applied on a dataset, which includes 180 2-D bullet images fired from 90 different AK-47 barrels. The experimentations showed that our approach attained better results compared to common methods in the field of bullet identification.<br><br>© 2018 American Academy of Forensic Sciences.<p /> <p>Language: en</p>",
language="en",
issn="0022-1198",
doi="10.1111/1556-4029.13956",
url="http://dx.doi.org/10.1111/1556-4029.13956"
}