Proposal for Method of Estimating Fruit Volume of Cherry Tomatoes Using 3D Image Measurement

In this study, an ortho image was generated from the 3D point cloud data of cherry tomatoes, and fruit regions were extracted using SegNet, a deep learning based semantic segmentation model. From the extracted fruit regions, a reconstructed 3D point cloud of each fruit was generated, and the occluded regions were complemented based on the fruit's geometric symmetry. The fruit volume was then estimated using the least-squares ellipsoidal approximation.