A Multimodal Fusion Approach for Bullet Identification Systems
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Bigdeli, Saeed [1] ; Ebrahimi Moghaddam, Mohsen [1]
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[1] Faculty of Computer Science and Engineering, Shahid Beheshti University.Iran
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- Localización: Journal of forensic sciences, ISSN-e 1556-4029, ISSN 0022-1198, Vol. 64, Nº. 3, 2019, págs. 741-753
- Idioma: inglés
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Resumen
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.
