Cartridge case image matching using effective correlation area based method

A firearm leaves a unique impression on fired cartridge cases. The cross-correlation function plays an important role in matching the characteristic features on the cartridge case found at the crime scene with a specific firearm, for accurate firearm identification. This paper proposes that the computational forensic techniques of alignment and effective correlation area-based approaches to image matching are essential to firearm identification. Specifically, the reference and the corresponding cartridge cases are aligned according to the phase-correlation criterion on the transform domain. The informative segments of the breech face marks are identified by a cross-covariance coefficient using the coefficient value in a window located locally in the image space. The segments are then passed to the measurement of edge density for computing effective correlation areas. Experimental results on a new dataset show that the correlation system can make use of the best properties of alignment and effective correlation area-based approaches, and can attain significant improvement of image-correlation results, compared with the traditional image-matching methods for firearm identification, which employ cartridge-case samples. An analysis of image-alignment score matrices suggests that all translation and scaling parameters are estimated correctly, and contribute to the successful extraction of effective correlation areas. It was found that the proposed method has a high discriminant power, compared with the conventional correlator. This paper advocates that this method will enable forensic science to compile a large-scale image database to perform correlation of cartridge case bases, in order to identify firearms that involve pairwise alignments and comparisons.