Use of Correlation algorithms in a database of spent cartridge cases of firearms

On the market several systems exist for collecting spent ammunition for forensic investigation. These databases store images of cartridge cases and the marks on them. The research in this paper is focussed on the different methods of feature selection and pattern recognition that can be used for computation For automatic comparison of these images are extracted firstly the useful parts of the images. On a database of 4966 images several preprocessing steps have been tested and compared. From this research it appeared that the equalization of greyvalues is a very good first step. We tested our algorithms using 19 matching pairs, were the ground truth was known that they were shot with the same firearm. In cases were the registration between those matching pairs was good, a simple computation of the standard deviation of the subtracted gray levels put the matching images on top of the hit list. For other ones, we have implemented a "robust" way of registration in all images are translated and rotated and the minimum of the standard deviation of the difference is computed. It appeared that this method worked if the firing pin marks are similar. Otherwise the firing pin should be handled separately from the breechface mark. By modifying the weight of the firing pin to 50 percent, it appeared that we had all images in the top list. The method will take much processing power. Since the shapes of the region of interest is circular it appeared to be useful to calculate in polar coordinates. For improving the computational speed, we have implemented a wavelet technique (a trous), in which four scales are calculated. From these scales, the third scale is used. The log polar transform on this third scale will reduce the computational effort involved. The matching images were in the top positions of the hit list.