Agricultural and Biosystems Engineering Publications

Campus Units

Agricultural and Biosystems Engineering, Human Computer Interaction, Plant Sciences Institute

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

6-2018

Journal or Book Title

Journal of Field Robotics

Volume

35

Issue

4

First Page

596

Last Page

611

DOI

10.1002/rob.21763

Abstract

A 3D time‐of‐flight camera was applied to develop a crop plant recognition system for broccoli and green bean plants under weedy conditions. The developed system overcame the previously unsolved problems caused by occluded canopy and illumination variation. An efficient noise filter was developed to remove the sparse noise points in 3D point cloud space. Both 2D and 3D features including the gradient of amplitude and depth image, surface curvature, amplitude percentile index, normal direction, and neighbor point count in 3D space were extracted and found effective for recognizing these two types of plants. Separate segmentation algorithms were developed for each of the broccoli and green bean plant in accordance with their 3D geometry and 2D amplitude characteristics. Under the experimental condition where the crops were heavily infested by various types of weed plants, detection rates over 88.3% and 91.2% were achieved for broccoli and green bean plant leaves, respectively. Additionally, the crop plants were segmented out with nearly complete shape. Moreover, the algorithms were computationally optimized, resulting in an image processing speed of over 30 frames per second.

Comments

This is the peer-reviewed version of the following article: Li, Ji, and Lie Tang. "Crop recognition under weedy conditions based on 3D imaging for robotic weed control." Journal of Field Robotics 35, no. 4 (2018): 596-611, which has been published in final form at DOI: 10.1002/rob.21763. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Copyright Owner

Wiley Periodicals, Inc.

Language

en

File Format

application/pdf

Published Version

Share

COinS