An intelligent imaging approach to the identification of forensic ballistics specimens

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.