Ballistic examinations based on 3D data: a comparative study of probabilistic Hough Transform and geometrical shape determination for circle-detection on cartridge bottoms

The application of contact-less optical 3D sensing techniques yielding digital data for the acquisition of toolmarks on forensic ballistic specimens found at crime scenes, as well as the development of computer-aided, semi-automated firearm identification systems that are using 3D information, are currently emerging fields of research with rising importance. Traditionally, the examination of forensic ballistic specimen is done manually by highly skilled forensic experts using comparison microscopes. A partly automation of the comparison task promises examination results that are less dependent on subjective expertise and furthermore a reduction of the manual work needed. While there are some partly automated systems available they are all of proprietary nature to our current knowledge. One necessary requirement for the examination of forensic ballistic specimens is a reliable circle-detection and segmentation of cartridge bottoms. This information is later used for example for alignment and registration tasks, determination of regions of interest, and locally restricted application of complex feature-extraction algorithms. In this work we are using a Keyence VK-X 105 laser-scanning confocal microscope to acquire a very high detail topography image, a laserintensity image, and a color image of the assessed cartridge bottoms simultaneously. The work is focused on a comparison of Hough Transform (21HT) and Geometric Shape Determination for circle-detection on cartridge bottoms using 3D as well as 2D information. We compare the pre-processing complexity, the required processing time, and the ability for a reliable detection of all desired circles. We assume that the utilization of Geometric Shape Detection can reduce the required processing time due to a less complex processing. For application of shape determination as well as for Hough Transform we expect a more reliable circle-detection when using additional 3D information. Our first experimental evaluation, using 100 9mm center fire cartridges shot from 3 different firearms shows positive tendency to verify these suppositions.