科研之友
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摘要
Labor cost and availability have been a major concern for tree fruit growers, as many field operations, including tree pruning, are highly labor intensive. Currently, pruning in apple production is primarily a manual operation. However, newer orchards are being planted in simple, narrow, accessible, and productive (SNAP) architectures such as the tall spindle fruiting wall system, which provides opportunities for automated pruning. This technical note presents a method to obtain the 3D structures of apple trees and identify branches as a first step toward developing an automated pruning system. A time-of-flight-of-light-based three-dimensional (ToF 3D) camera is used to obtain 3D images of apple trees in a commercial orchard. The images are preprocessed to remove noise and fill unwanted voids. The preprocessed images are then used to generate tree skeletons using a medial axis thinning algorithm. Tree skeletons are analyzed to detect trunks and identify branches. This method successfully reconstructed 3D structures of apple trees with 100% accuracy in detecting trunks. The method achieved a branch identification accuracy of 77%, with a false negative identification of 23%. This work provides a promising method for 3D reconstruction of apple trees that can be used to generate a database of tree branches including branch length and interbranch spacing, which is critical information for developing a system for automated pruning.
- 出版日期2015
