Abstract
In agriculture, information about the spatial distribution of plant growth is valuable for applications. Quantitative study of the characteristics of plants plays an important role in the plants’ growth and development research, and non-destructive measurement of the height of plants based on machine vision technology is one of the difficulties. We propose a methodology for three-dimensional reconstruction under growing plants by Kinect v2.0 and explored the measure growth parameters based on three-dimensional (3D) point cloud in this paper. The strategy includes three steps—firstly, preprocessing 3D point cloud data, completing the 3D plant registration through point cloud outlier filtering and surface smooth method; secondly, using the locally convex connected patches method to segment the leaves and stem from the plant model; extracting the feature boundary points from the leaf point cloud, and using the contour extraction algorithm to get the feature boundary lines; finally, calculating the length, width of the leaf by Euclidean distance, and the area of the leaf by surface integral method, measuring the height of plant using the vertical distance technology. The results show that the automatic extraction scheme of plant information is effective and the measurement accuracy meets the need of measurement standard. The established 3D plant model is the key to study the whole plant information, which reduces the inaccuracy of occlusion to the description of leaf shape and conducive to the study of the real plant growth status.
Highlights
With the development of protected vegetable production, vegetable seedlings are increasingly recognized by producers, which has become an important pillar of vegetable industry development.In agriculture, information about the spatial distribution of crop growth is valuable for applications such as biomass and yield estimation or increasing field work efficiency in terms of fertilizing, applying pesticides and irrigation [1,2]
Using the Euclidean distance [9,10] to present the plant height is commonly used on 2D images, extracting the plant skeleton on the region of interest (ROI) and detecting the lowest and highest points of the skeleton
A Kinect camera and an electric turntable were used to build a 3D plant model according to the following instructions
Summary
With the development of protected vegetable production, vegetable seedlings are increasingly recognized by producers, which has become an important pillar of vegetable industry development. Using the Euclidean distance [9,10] to present the plant height is commonly used on 2D images, extracting the plant skeleton on the region of interest (ROI) and detecting the lowest and highest points of the skeleton. With the development of three-dimensional vision, more researchers segment the main organs of the plant after reconstruction the whole plant, extract the leaves, and study morphological features of leaves. Some researchers have developed measurement systems to reconstruct 3D point cloud for plant of growth information [32,33,34,35,36], for example, Andújar et al [37] explored the possibilities of using.
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