Agricultural and Biosystems Engineering Publications

Document Type

Article

Publication Date

2008

Journal or Book Title

Transactions of the ASABE

Volume

51

Issue

3

First Page

1079

Last Page

1087

Research Focus Area(s)

Advanced Machinery Engineering and Manufacturing Systems

Abstract

In-field variations in corn plant spacing and population can lead to significant yield differences. To minimize these variations, seeds should be placed at a uniform spacing during planting. Since the ability to achieve this uniformity is directly related to planter performance, intensive field evaluations are vitally important prior to design of new planters and currently the designers have to rely on manually collected data that is very time consuming and subject to human errors. A machine vision-based emerged crop sensing system (ECSS) was developed to automate corn plant spacing measurement at early growth stages for planter design and testing engineers. This article documents the first part of the ECSS development, which was the real-time video frame mosaicking for crop row image reconstruction. Specifically, the mosaicking algorithm was based on a normalized correlation measure and was optimized to reduce the computational time and enhance the frame connection accuracy. This mosaicking algorithm was capable of reconstructing crop row images in real-time while the sampling platform was traveling at a velocity up to 1.21 m s-1 (2.73 mph). The mosaicking accuracy of the ECSS was evaluated over three 40 to 50 m long crop rows. The ECSS achieved a mean distance measurement error ratio of -0.11% with a standard deviation of 0.74%.

Comments

This article is from Transactions of the ASABE 51, no. 3 (2008): 1079–1087.

Copyright Owner

American Society of Agricultural and Biological Engineers

Language

en

Date Available

April 2, 2013

File Format

application/pdf

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