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Presentation
Plant Recognition through the Fusion of 2D and 3D Images for Robotic Weeding
Agricultural and Biosystems Engineering Conference Proceedings and Presentations
  • Jingyao Gai, Iowa State University
  • Lie Tang, Iowa State University
  • Brian L. Steward, Iowa State University
Document Type
Conference Proceeding
Publication Version
Published Version
Publication Date
7-1-2015
DOI
10.13031/aim.20152181371
Conference Title
2015 ASABE Annual International Meeting
Conference Date
July 26–29, 2015
Geolocation
(29.95106579999999, -90.0715323)
Abstract

In crop production systems, weed management is vitally important. But both manual weeding and herbicide-based weed controlling are problematic due to concerns in cost, operator health, emergence of herbicide-resistant weed species, and environment impact. Automated robotic weeding offers a possibility of controlling weeds in a precise fashion, particularly for weeds growing near crops or within crop rows. However, identification and localization of plants have not yet been fully automated. The goal of this reported project is to develop a high-throughput plant recognition and localization algorithm by fusing 2D color and textural data with 3D point cloud data. Plant morphological models were developed and applied for plant recognition against different weed species at different growth stages.

Comments

This proceeding is from 2015 ASABE Annual International Meeting, Paper No. 152181371, pages 1-8 (doi: 10.13031/aim.20152181371). St. Joseph, Mich.: ASABE.

Copyright Owner
American Society of Agricultural and Biological Engineers
Language
en
File Format
application/pdf
Citation Information
Jingyao Gai, Lie Tang and Brian L. Steward. "Plant Recognition through the Fusion of 2D and 3D Images for Robotic Weeding" New Orleans, LA, United States(2015)
Available at: http://works.bepress.com/lie_tang/18/