Performance Evaluation of Low-Cost 3D Scanning Techniques

This study evaluates the performance of three low-cost 3D scanning techniques: structured light sensors (using a Kinect and a CR-Scan Ferret) and photogrammetry, to capture 3D-printed physical models. The research compares the resulting 3D models with the original digital models to assess each technique's accuracy and the effectiveness of low-cost methods. The study’s workflow involved printing four 3D models, scanning them, and comparing the models using similarity metrics like Hausdorff distance, RMSE, and Chamfer distance. The CR-Scan Ferret generally outperformed the other methods, particularly in capturing detail. However, it sometimes produced gaps that required filling. Photogrammetry was a viable alternative, excelling at preserving object shapes without creating gaps. The Kinect, while accessible, consistently delivered the lowest performance, struggling to reproduce object details and forms accurately.