Agricultural and Biosystems Engineering Publications

Document Type

Article

Publication Date

2008

Journal or Book Title

Transactions of the ASABE

Volume

51

Issue

6

First Page

2181

Last Page

2191

Research Focus Area(s)

Advanced Machinery Engineering and Manufacturing Systems

Abstract

Image processing algorithms for individual corn plant and plant stem center identification were developed. These algorithms were applied to mosaicked crop row image for automatically measuring corn plant spacing at early growth stages. These algorithms utilized multiple sources of information for corn plant detection and plant center location estimation including plant color, plant morphological features, and the crop row centerline. The algorithm was tested over two 41 m (134.5 ft) long corn rows using video acquired two times in both directions. The system had a mean plant misidentification ratio of 3.7%. When compared with manual plant spacing measurements, the system achieved an overall spacing error (RMSE) of 1.7 cm and an overall R2 of 0.96 between manual plant spacing measurement and the system estimates. The developed image processing algorithms were effective in automated corn plant spacing measurement at early growth stages. Interplant spacing errors were mainly due to crop damage and sampling platform vibration that caused mosaicking errors.

Comments

This article is from Transactions of the ASABE 51, no. 6 (2008): 2181–2191.

Copyright Owner

American Society of Agricultural and Biological Engineers

Language

en

Date Available

April 2, 2013

File Format

application/pdf

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