Recently, one of the central issues in the fields of Photogrammetry, Computer Vision, Computer Graphics and Image Processing is the development of tools for the automatic reconstruction of complex 3D objects. Among various approaches, one of the most promising is Structured Light 3D scanning (SL) which combines automation and high accuracy with low cost, given the steady decrease in price of cameras and projectors. SL relies on the projection of different light patterns, by means of a video projector, on 3D object sur faces, which are recorded by one or more digital cameras. Automatic pattern identification on images allows reconstructing the shape of recorded 3D objects via triangulation of the optical rays corresponding to projector and camera pixels. Models draped with realistic phototexture may be thus also generated, reproducing both geometry and appearance of the 3D world. In this context, subject of our research is a synthesis of state-of-the-art as well as the development of novel algorithms, in order to implement a 3D scanning system consisting, at this stage, of one consumer digital camera (DSLR) and a video projector. In the following, the main principles of structured light scanning and the algorithms implemented in our system are presented, and results are given to demonstrate the potential of such a system. Since this work is part of an ongoing research project, future tasks are also discussed.
LiDARPheno – A Low-Cost LiDAR-Based 3D Scanning System for Leaf Morphological Trait Extraction