A Multimodal Fusion Approach for Bullet Identification Systems

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.