Abstract
Fingerprints and microtraces play an important role as evidence within the field of criminalistics. Their conservative acquisition processes, are established, but are altering and impurifying the traces often. In case of microtraces even the integrity of the trace complex is affected. Using contactless methods, the acquisition process becomes non-invasiv and repeatable, but might be distorting on the other hand, when non-planar substrates are in use. Detecting and dealing with distortion in contactless aquired scans of non-planar surfaces is a novel field of research. Nowadays highly distorted fingerprints can only be used, if the substrate can be manually distorted by destroying or deforming it. In this paper we suggest methods for detection and equalization of distortion for use in combination of types of traces. Therefore we define different types of distortion in fingerprints and microtraces. A standardization of types is necessary to develop different solution for equalization. For usage within the field of forensics, each method is evaluated via proper error rates and adaptively used to acquire fingerprints and microtraces. Using our techniques, we are able to detect distortion and equalize fingerprints to support the investigators work. In case of microtraces the presented methods can even be used to equalize mircotraces themselves for better determination of their scale and topology. For all scans the confocal 3D laser microscope
"Keyence VK-X110" is used to gather color-, intensity- and topography information in 22 different measurement conditions within 6 different samples consisting of a total of 880 scans. Despite our achievements in the field of distortion detection and equalization there are still challenges, like the non-isometric projection, that need to be focused on. Also, the presented equalization methods may not completely remove any kind of distortion, such as added by deformation. Therefore we suggest and discuss future work for improving the distortion detection process by adding classification of sources of distortion to assure that the correct equalization method is used.
