Document Type
Conference Proceeding
Publisher
IEEE
Faculty
Faculty of Computing, Health and Science
School
School of Engineering and Mathematics
RAS ID
1749
Abstract
The characteristic markings on the cartridge and projectile of a bullet fired from a gun can be recognised as a "fingerprint" for identification of the firearm. Over thirty different features can be distinguished. The intelligent imaging of the class characteristics of ballistics specimens will provide the potential to identify the make and model of the firearm. Precise measurement of features allow ballistics metrics to be obtained for the identification of the weapon. This paper will describe progress in the development of a multidimensional cluster analysis model for forensic ballistics specimens. The cluster analysis will provide classification that is based on scalar shape and measurement parameters for the 3D features of class characteristics. The selection of appropriate class characteristics for cartridge and projectile can be mapped in N-dimensional space to provide clustering for particular weapon types. By mapping the crime scene specimen to the multidimensional ballistics data, the possibility of a match for identification can be achieved
DOI
10.1109/ICII.2001.983088
Access Rights
free_to_read
Comments
This is an Author's Accepted Manuscript of: Smith, C. L. (2001). An intelligent imaging approach to the identification of forensic ballistics specimens. Proceedings of 2001 International Conferences of Info-Tech and Info-Net. (pp. 390 - 396). Beijing, China. IEEE. Available here
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