Title

A new approach for firearm identification with hierarchical neural networks based on cartridge case images

Document Type

Conference Proceeding

Publisher

IEEE

School

School of Computer and Information Science

Comments

Li, D. (2006, July). A new approach for firearm identification with hierarchical neural networks based on cartridge case images. In 2006 5th IEEE International Conference on Cognitive Informatics (Vol. 2, pp. 923-928). IEEE.

https://doi.org/10.1109/COGINF.2006.365616

Abstract

When a gun is fired, characteristic markings on the cartridge and projectile of a bullet are produced. Over thirty different features can be distinguished from observing these marks, which in combination produce a "fingerprint" for identification of a firearm. In this paper, through the use of hierarchial neural networks a firearm identification system based on cartridge case images is proposed. We focus on the cartridge case identification of rim-fire mechanism. Experiments show that the model proposed has high performance and robustness by integrating two levels self-organizing feature map (SOFM) neural networks and the decision-making strategy. This model will also make a significant contribution towards the further processing, such as the more efficient and precise identification of cartridge cases by combination with more characteristics on cartridge cases images

DOI

10.1109/COGINF.2006.365616

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Link to publisher version (DOI)

10.1109/COGINF.2006.365616