The diversity of arthropods is unparalleled ( Misof et al., 2014). The resulting accessibility of scAnt will (i) drive the development of novel and powerful methods for machine learning-driven behavioural studies, leveraging synthetic data (ii) increase accuracy in comparative morphometric studies as well as extend the available parameter space with area and volume measurements (iii) inspire novel forms of outreach and (iv) aid in the digitisation efforts currently underway in several major natural history collections. As a result of the exclusive reliance on generic hardware components, rapid prototyping and open-source software, scAnt costs only a fraction of available comparable systems. We demonstrate how these 3D models can be rigged to enable realistic digital specimen posing, and introduce a novel simple yet effective method to include semi-realistic representations of approximately planar and transparent structures such as wings. The masked images can then be processed further with a photogrammetry software package of choice, including open-source options such as Meshroom, to create high-quality, textured 3D models. ![]() These images are then masked with a novel automatic routine which combines random forest-based edge-detection, adaptive thresholding and connected component labelling. scAnt consists of a scanner and a Graphical User Interface, and enables the automated generation of Extended Depth Of Field images from multiple perspectives. ![]() We present scAnt, an open-source platform for the creation of digital 3D models of arthropods and small objects.
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