A New Approach for Firearm Identification with Hierarchical Neural Networks Based on Cartridge Case Images

摘要：

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 ofhierarchial 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 Jurther processing, such as the more efficient and precise identification of cartridge cases by combination with more characteristics on cartridge cases images.

关键词： Firearm identification Neural networks Image processing.

作者: Dongguang Li

作者单位: School of Computer and Information Science Edith Cowan University 2 Bradford Street, Mount Lawley 6050 Perth, Western Australia

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 923-928

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）