This article presents a description of the development and capabilities of a fully automated prototype of a three-dimensional imaging system for footwear and tire tread impressions that performs better than current casting techniques due to being non-destructive and collecting more evidence detail while costing less per piece of evidence and producing an easily shared digital file.
Dr. Song Zhang and his research team at Purdue University led the development of a fully automated 3D imaging system for footwear and tire tread impressions. In comparison to current casting techniques, the fully automated prototype "demonstrates its superiority because it (1) is non-destructive; (2) collects more evidence detail than casts, especially when an impression is fragile; (3) requires less time and money to collect each piece of evidence; and (4) results in a digital file that can easily be shared with other examiners."1 The NIJ's Forensic Technology Center of Excellence (FTCoE) evaluated this prototype 3D imaging system's performance in a real-world setting with the assistance of footwear and tire examiners at three U.S. crime laboratories. The examiners were asked to provide their assessment on whether (1) the scanner was field ready, (2) the virtual impressions reproduced the footwear/tire evidence impressions accurately and precisely, (3) the 3D technology fits into examination processes and laboratory capabilities, and (4) they would purchase this technology in its current form.
1: Yi-Hong Liao, Jae-Sang Hyun, Michael Feller, Tyler Bell, Ian Bortins, James Wolfe, David Baldwin, Song Zhang. (2020). Portable high-resolution automated 3D imaging for footwear and tire impression capture. Journal of Forensic Science, Vol. 66, No. 1.