Document Type

Conference Proceeding


Edith Cowan University

Place of Publication

Western Australia


Faculty of Computing, Health and Science


School of Computer and Information Science




Li, D. (2007). Li, D. (Ed.). Firearm identification with hierarchical neural networks by analyzing the firing pin images retrieved from cartridge cases. In Li, D. Proceedings of the Sixth International Workshop for Applied PKC (IWAP2007), Mt. Lawley Campus, Edith Cowan University, 3rd-4th December, 2007. Western Australia: Edith Cowan University. pp.70-78


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. ln 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