Automatic Leaf Segmentation for Estimating Leaf Area and Leaf Inclination Angle in 3D Plant Images.

Kenta Itakura,Fumiki Hosoi

doi:10.3390/s18103576

Abstract

Automatic and efficient plant monitoring offers accurate plant management. Construction of three-dimensional (3D) models of plants and acquisition of their spatial information is an effective method for obtaining plant structural parameters. Here, 3D images of leaves constructed with multiple scenes taken from different positions were segmented automatically for the automatic retrieval of leaf areas and inclination angles. First, for the initial segmentation, leave images were viewed from the top, then leaves in the top-view images were segmented using distance transform and the watershed algorithm. Next, the images of leaves after the initial segmentation were reduced by 90%, and the seed regions for each leaf were produced. The seed region was re-projected onto the 3D images, and each leaf was segmented by expanding the seed region with the 3D information. After leaf segmentation, the leaf area of each leaf and its inclination angle were estimated accurately via a voxel-based calculation. As a result, leaf area and leaf inclination angle were estimated accurately after automatic leaf segmentation. This method for automatic plant structure analysis allows accurate and efficient plant breeding and growth management.

Highlights

In the growth and developmental processes, plant structures change during the seasons because of environmental processes [1]
We propose methods for accurate and automatic leaf segmentation and retrieval of plant structural parameters using 3D point-cloud images, overcoming disadvantages of previous studies
Initial segmentation was conducted based on the top-view images of plants using distance transform and the watershed algorithm

Summary

Introduction

In the growth and developmental processes, plant structures change during the seasons because of environmental processes [1]. For accurate plant breeding and growth monitoring, it is necessary to obtain information about the plant structures affecting the plant status [2,3,4]. Leaf area index (LAI) is an important plant structural parameter because it determines the primary photosynthetic production, plant evaporation, and plant growth characterization [5]. Leaf inclination angle can be an informative plant structural parameter because it can be an indicator of a growth-state, such as a water condition [6]. LAI and leaf inclination angles are important plant structural parameters. The conventional methods of measuring LAI and leaf inclination angles are destructive and tedious [5,8]

Methods

Results

Discussion

Conclusion