Law enforcement has a new tool to help bring criminals to justice, thanks to research by scientists at the US Department of Energy’s Ames Laboratory.
When tools such as screwdrivers, pliers and wire cutters are manufactured, the manufacturing process leaves certain imperfections, or patterns, embedded in the tools’ surfaces. Because these patterns are believed to be unique for each tool, when criminals use them to perpetrate crimes, such as jimmying a door to gain access to a location, the patterns on the tools are often transferred to the crime scene.
In the past, investigators have been able to help the courts convict criminals by visually matching the marks on tools to crime scenes. But this technique is under attack. In a landmark 2000 case, a Florida court deemed a toolmark inadmissible, saying the “proposition of uniqueness” for a knife blade based on marks transferred to a victim was a scientific theory that had been inadequately tested by the scientific community.
Two research projects at the Ames Laboratory have responded to the challenge in an attempt to establish toolmark uniqueness. The first project, spearheaded by Stan Bajic, Ames Laboratory associate scientist, and David Baldwin, director of the Laboratory’s Midwest Forensics Resource Centre, involved building a database of toolmark images and developing an algorithm to statistically analyse the images. The database consists of digital images of marks on tool surfaces left during six different manufacturing processes.
Building of the database required the production of multiple images using a forensic comparison microscope. Researchers included numerous tools in their research, from screwdrivers, pliers and wire cutters to bolt cutters, tin snips, cold chisels, wood chisels and pry bars. So far, 13,000 images have been produced for the database.
The images produced were used in the development of a software tool for the reduction and analysis of the image data. Algorithms were developed and used for comparison of the various toolmarks by Max Morris, Ames Laboratory associate and Iowa State University professor of statistics and industrial engineering, and Zhigang Zhou, a graduate student in statistics. Morris’ software can mimic the behaviour of the forensic examiners.
“Our preliminary results have been very encouraging,” said Morris. “In the vast majority of cases, the algorithm correctly identifies images taken from different surfaces as non-matches. It also correctly identifies most pairs of images taken from a common surface as matches.” Morris calls the results “an important first step” in the effort to develop tools to determine the uniqueness of toolmarks.”
In a third research project, Scott Chumbley, an Ames Laboratory metallurgist and ISU professor of materials science and engineering, is taking toolmark analysis from the two-dimensional to three-dimensional level.
Chumbley and co-principal investigator Larry Genalo are using 3-D characterisation methods and statistical methods to identify toolmarks. Their research involves using a profilometer, a scanning tool that measures the height or depth of toolmarks, and then develops a type of contour map of the marks from the scan.
The map can then be used to precisely identify a toolmark, allowing forensic specialists to match the mark on the tool to the marks made by the tool at the crime scene. According to Chumbley, “Preliminary results show the reproducibility of the instrument is better than 99.9 percent on known samples.”