Machine Vision Systems for Real-Time Plant Variability Sensing and in-Field Application
Tang, Lie
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https://hdl.handle.net/2142/86047
Description
Title
Machine Vision Systems for Real-Time Plant Variability Sensing and in-Field Application
Author(s)
Tang, Lie
Issue Date
2002
Doctoral Committee Chair(s)
Lei Tian
Department of Study
Agricultural Engineering
Discipline
Agricultural Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Agriculture, Agronomy
Language
eng
Abstract
In-field variations associated with corn plant spacing, growth stage, and population can lead to a significant yield differences. Since the ability to reduce these variations is directly related to the planter performance, a machine vision-based emerged corn plant sensing system (ECS) was developed for the performance evaluation for prototype planters. With the real-time image sequencing capability, the system also achieved an average spacing measurement error of less than 10 mm.
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