On the market several systems exist for collecting spent ammunition data for forensic investigation. These databases store images of cartridge cases and the marks on them. Image matching is used to create hit lists that show those cartridges in the database which have marks that are most similar to the marks of the cartridge case under investigation. The research in this paper focuses on the different methods of feature selection and pattern recognition that can be used for optimizing the results of image matching. A fast pre-selection method based on signatures is applied that is based on the Kanade Lucas Tomasi (KLT) equation. The positions of the points computed with this method are compared. In this way 11 of the 49 images were in the top position in combination with the third scale of the à trous wavelet. Light conditions and the prominence of the marks determines to a large extent whether correct matches are found in the top ranked position. All images were retrieved in the top five percent of the complete database. This method takes only a few minutes, which can be structured for comparisons to be carried out in seconds.