# Automated classification of stems and leaves of potted plants based on point cloud data

arXiv: https://arxiv.org/abs/2002.12536 · HTML: https://mlsanity.com/paper/2002.12536/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Feb 2020.

## Built on by (most cited first, 1 of 1)

- [Wood-leaf classification of tree point cloud based on intensity and geometrical information](https://mlsanity.com/paper/2108.01002/) (2021)

## Abstract (arXiv)

The accurate classification of plant organs is a key step in monitoring the growing status and physiology of plants. A classification method was proposed to classify the leaves and stems of potted plants automatically based on the point cloud data of the plants, which is a nondestructive acquisition. The leaf point training samples were automatically extracted by using the three-dimensional convex hull algorithm, while stem point training samples were extracted by using the point density of a two-dimensional projection. The two training sets were used to classify all the points into leaf points and stem points by utilizing the support vector machine (SVM) algorithm. The proposed method was tested by using the point cloud data of three potted plants and compared with two other methods, which showed that the proposed method can classify leaf and stem points accurately and efficiently.