# Realization of Impression Evidence with Reverse Engineering and Additive Manufacturing
## 1 Introduction
Therefore, the aforementioned technological limitations associated with traditional casting and 2D photography in reconstruction of impression evidence highlight the importance of employing new 3D technologies like reverse engineering and additive manufacturing for digital and physical 3D reconstruction. Currently, the 3D digital and physical reconstruction of 3D impression is growing rapidly, but the concept of 3D reconstruction of impressions based on 2D photos and its potential utilization are still limited in the field of forensic analysis, but with the advent of 3D technologies, this concept is gaining attention. Figure 1: Examples of impression evidence types: (**a**) 3D tire–footwear plastic impression in dry sand; (**b**) 2D latent fingerprint developed on aluminum foil [12]; (**c**) 2D visible footwear impression (courtesy of [PERSON], Ron Smith & Associates, Inc. (Collinsville, MS, USA)). In recent years, rapid advancements in 3D technologies have impacted various sectors such as industry, medicine, and culture. Access to realization of the world in 3D is no longer confined to expensive facilities. The key pillars of these technologies include 3D scanning, modeling software, and additive manufacturing. 3D scanning is the process of acquiring geometrical and possibly texture color data for an object or environment to generate its corresponding 3D digital model. 3D data can be acquired through many available techniques. Figure 2 shows a classification for 3D scanning techniques. In forensic applications, acquiring 3D scans of crime scenes typically involves costly and specialized equipment like computed tomography (CT) and professional laser scanners. These tools demand extensive training and are often inaccessible [16; 17; 18]. However, recent advancements in consumer scanning devices, such as SL scanners, handheld LS, RGB-D systems, and iPhone's LiDAR (iLiDAR) Scanners, alongside SP photogrammetry, have sparked interest within the forensic community. These alternatives offer affordability, ease of use, and time efficiency compared to their high-tech counterparts. Figure 2: Classification for 3D scanning techniques. While researchers increasingly explore 3D scanning in forensic applications [15; 17; 19; 20; 21], most studies focus on standalone 3D reconstruction methods for impression evidence. These include laser scanning [6], structured-light scanning [22; 23], smartphone photometry [24], RGB-D scanning [25], and iPhone's LiDAR [17], and only a few studies compared the use of different low-cost consumer-level devices exist for impression evidence scanning. However, comparing various scanning techniques helps identify the most accurate method for producing high-quality 3D impression models. In this work, we compare five non-contact surface scanning methods: handheld laser scanning, structured-light scanning, smartphone photogrammetry, Kinect v2 RGB-D scanning, and iPhone's LiDAR (iLiDAR) in the 3D reconstruction of plastic impression evidence. Additive manufacturing (AM) is another 3D technology that has gained attention in the forensic community due to its ability to reconstruct patterns and devices quickly and at various scales for forensic applications. ASTM F2792-12a [26] defines AM as the process of joining materials to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies. AM encompasses automated techniques like Fused Deposition Modelling (FDM), Selective Laser Sintering (SLS), Stereolithography (SLA), Selective Laser Melting (SLM), and Three-Dimensional Printing (3 DP), which are categorized according to classification Illustrated in Figure 3.  
The AM process begins with creating a 3D computer-aided design (CAD) file for the part, which is then converted to \".STL\" (StereoLithography) format to approximate the model's surfaces with a triangle mesh. Next steps include setting part orientation, support creation, virtual slicing into thin layers, toolpath generation, and G-code creation.