Optimization of 3D Point Clouds of Oilseed Rape Plants Based on Time-of-Flight Cameras

Abstract

Three-dimensional (3D) structure is an important morphological trait of plants for describing their growth and biotic/abiotic stress responses. Various methods have been developed for obtaining 3D plant data, but the data quality and equipment costs are the main factors limiting their development. Here, we propose a method to improve the quality of 3D plant data using the time-of-flight (TOF) camera Kinect V2. A K-dimension (k-d) tree was applied to spatial topological relationships for searching points. Background noise points were then removed with a minimum oriented bounding box (MOBB) with a pass-through filter, while outliers and flying pixel points were removed based on viewpoints and surface normals. After being smoothed with the bilateral filter, the 3D plant data were registered and meshed. We adjusted the mesh patches to eliminate layered points. The results showed that the patches were closer. The average distance between the patches was 1.88 × 10−3 m, and the average angle was 17.64°, which were 54.97% and 48.33% of those values before optimization. The proposed method performed better in reducing noise and the local layered-points phenomenon, and it could help to more accurately determine 3D structure parameters from point clouds and mesh models.

Fast Reconstruction Method of Three-dimension Model Based on Dual RGB-D Cameras for Peanut Plant

“…Although the image quality requirement can be reduced in the SfM method, there is a lot of data redundancy in multiple images and the reconstruction speed is slow [32]. It is a widely used technique for reconstructing a 3D canopy using scanning equipment to generate a 3D point cloud of plants, which generally employs the ToF or phase-shifting scanning principle to generate the point cloud [33]. Shi et al [34] used LiDAR to create 3D models of corn plants and enable realtime monitoring of crops' 3D information.…”

“…However, it is not a feasible measurement of those traits under the field conditions, so the researchers tend to conduct the initial screening of breeds in a controlled environment because the changes in the process of crop growth can be found more intuitively [23,50,51]. As an RGB-D camera, Kinect v2 shows great potential with low cost and strong robustness in 3D modeling indoors [27,52], and it has been applied to 3D fine modeling of plants [33,[53][54][55].…”

Three-Dimensional Reconstruction Method of Rapeseed Plants in the Whole Growth Period Using RGB-D Camera

“…The point cloud is removed based on the normal of the viewpoint and the surface, which improves the quality of the point cloud and the accuracy of the subsequent point cloud registration. However, the effect of this algorithm on the removal of floating noise point needs to be improved [ 22 ]. Xu et al proposed a 3D scanning reconstruction system with multiple RGB-D cameras (Xtion sensors).…”

“…The RGB-D camera represented by Kinect is more balanced in three aspects: point cloud accuracy, cost and processing speed. It has been more and more widely used in fields such as 3D reconstruction [ 22 ], target recognition [ 1 ], nondestructive measurement [ 25 ], plant phenotype [ 24 ] and so on. Regardless of which 3D reconstruction method is applied to plant phenotype detection, a registration algorithm is required to unify the point clouds from different coordinate systems into the same coordinate system to eliminate the occlusion and obtain a complete point cloud.…”

Using Virtual Scanning to Find Optimal Configuration of a 3D Scanner Turntable for Scanning of Mechanical Parts

“…Non-contact active technologies include two basic groups of technologies—time of flight and triangulation. Time-of-flight scanners use laser rays to progressively probe the scanned surface [ 10 ], whereas time-of-flight cameras are able to provide a full 2D image with a depth component in a single operation [ 11 ] usually using a built-in shutter (range-gated imagers [ 12 ]) or modulated light [ 13 ]. Triangulation-based 3D scanners use a combination of a laser emitter that emits laser points or strips and a detector located in offset positions [ 14 ].…”