Footwear and tire impressions are critical evidence commonly found at a crime scene. However, they are often undervalued because they are hard to be captured and documented. Traditional 2D evidence quality photographs do not adequately provide metric depth information, and physical casts destroy the evidence afterward. Therefore, the forensic science community raised the need for improved evidence recognition, collection, and visualization analytical instrumentation for field and lab use. While the 3D optical techniques for imaging static objects have been extensively studied, there is still a major gap between current knowledge and collecting high-quality footwear and tire impressions evidence. Among optical means for 3D imaging, digital fringe projection (DFP) techniques reconstruct 3D shape from phase information, achieving camera-pixel spatial resolution. This paper presents a high-resolution 3D imaging technology using DFP techniques dedicated to footwear and tire impression capture. We developed fully automated software algorithms and a graphical user interface (GUI) that allow anyone without training to operate for high-quality 3D data capture. We performed accuracy evaluations and comparisons comparing with the commercial high-end 3D scanner and carried out qualitative tests for various impressions comparing with the current practices. Overall, our technology achieves similar levels of accuracy and resolution with a high-end commercially available 3D scanner, while having the merits of being 1) more affordable; 2) much easier to operate, and 3) more robust. Compared with the current practice of casting, our technology 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.<br>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/13277882 |
| Date | 16 December 2020 |
| Creators | Yi-Hong Liao (9675617) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/PORTABLE_HIGH-RESOLUTION_AUTOMATED_3D_IMAGING_FOR_FOOTWEAR_AND_TIRE_IMPRESSION_CAPTURE/13277882 |
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