The performance of BALISTIKA 2010 system for 9 mm × 19 mm and 7.65 mm × 17 mm cartridge case correlation.

The firearm identification has two examination phases; the first phase is "one by one" cartridge case or bullet identification. The second phase is "Open Case File (OCF)" examination. Due to the size of the OCF archive, the OCF examination with only comparison microscopes takes a long time and is an unfeasible process. The Computerized Ballistic Identification Systems (CBIS) has become an essential tool for archive examination by correlation and preliminary eliminations. In this study, two objectives were pursued; the first is measuring the performance of the BALISTIKA 2010 system on cartridge case acquisition of handguns, correlation and examination. The second objective is the examination of the performance on the correlation according to brand and models of firearms. Detailed experimental results are demonstrated for about 2000 cartridge cases.

Automated region segmentation on cartridge case base.

One of the significant problems encountered in criminology studies is the successful automated matching of fired cartridge cases, on the basis of the characteristic marks left on them by firearms. An intermediate step in the solution of this problem is the segmentation of certain regions that are defined on the cartridge case base. This paper describes a model-based method that performs segmentation of the cartridge case using surface height image of a center fire cartridge case base. The proposed method detects the location of the cartridge case base center and specific circular contours around it iteratively by projecting the problem to a one-dimensional feature space. In addition, the firing pin impression region is determined by utilizing an adaptive threshold that differentiates impression marks form primer region surface. Letters on the cartridge case base are also detected by using surface modeling and adaptive thresholding, in order to render the surface comparison operation robust against irrelevant surface features. Promising experimental results indicate the eligibility of the proposed method to be used for automated cartridge case base region segmentation process.

Three-dimensional surface reconstruction for cartridge cases using photometric stereo.

In forensic science, automated firearms identification is an important and yet unsolved problem. On the way to the solution, one of the most important phases is data acquisition. To be able to identify firearms in a reliable way, all the striated and impressed marks on metallic surfaces of cartridge cases should be visible. But two-dimensional images of cartridge cases are very sensitive to the type and direction of the light source(s). Depending on illumination conditions, the images of marks change drastically and sometimes they simply disappear. But, if the three-dimensional (3D) topography of the surface is obtained, the geometry of the marks, which is independent of the illumination, is available. Thus, by providing illumination independent features that can be used for automated matching, 3D data have the potential to make automated matching much reliable. In the literature on data acquisition for automated firearms identification, a few different ways of three-dimensional surface extraction are described, like laser interferometry or laser profilometry. This study presents a real life application of another method, photometric stereo, for the acquisition of 3D topographic data for cartridge cases, which is the one used in BALISTIKA Ballistics Image Analysis and Recognition System. In order to construct 3D topographic data, first of all, two-dimensional images were acquired using a specially designed set-up. After the images were calibrated radiometrically, photometric stereo method was applied. In order to minimize the low-frequency errors in the final surface, a surface-fitting algorithm was used. The method uses low-cost equipment and image acquisition is not time-consuming. Results were compared to interferometric measurement values for error assessment.