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Title:Machine Vision Systems for Real-Time Plant Variability Sensing and in-Field Application
Author(s):Tang, Lie
Doctoral Committee Chair(s):Lei Tian
Department / Program:Agricultural Engineering
Discipline:Agricultural Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Agriculture, Agronomy
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.
Issue Date:2002
Type:Text
Language:English
Description:150 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.
URI:http://hdl.handle.net/2142/86047
Other Identifier(s):(MiAaPQ)AAI3044237
Date Available in IDEALS:2015-09-28
Date Deposited:2002


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