Agricultural and Biosystems Engineering Publications
Campus Units
Agricultural and Biosystems Engineering, Human Computer Interaction
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
10-2004
Journal or Book Title
Biosystems Engineering
Volume
89
Issue
2
First Page
119
Last Page
129
Research Focus Area(s)
Land and Water Resources Engineering
DOI
10.1016/j.biosystemseng.2004.06.007
Abstract
Algorithms were developed to process video of maize rows and extract plant features to estimate density and spacing of early growth stage maize plants. The Otsu method was modified to compensate for varied amount of plant segmentation noise presented in different operating conditions. Three features were extracted and used to differentiate between weeds and maize plants: projected plant canopy area, plant length in the image row direction, and perpendicular distance of estimated plant centres from the mean crop row position. Algorithm performance was analysed across three tillage treatments, three growth stages, and three target populations varying from 27 000 to 81 500 plants ha−1. Overall, the algorithm estimated the number of plants in 6·1 m crop row sections with a root mean squared error of 2·1 plants or 8·7% of the mean manual count of 24·1 plants per experimental unit. The mean measurement error was significantly different across tillage treatments, but no evidence of significant differences was found across growth stages and plant populations. The error variance at the vegetative growth stages with the seventh or eight leaf collar visible was significantly higher than that at the growth stages with the third or fourth leaf collar visible. No significant differences were found between mean measured and estimated plant spacing distances.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Copyright Owner
Silsoe Research Institute
Copyright Date
2004
Language
en
File Format
application/pdf
Recommended Citation
Shrestha, D. S.; Steward, Brian L.; and Birrell, Stuart J., "Video Processing for Early Stage Maize Plant Detection" (2004). Agricultural and Biosystems Engineering Publications. 1098.
https://lib.dr.iastate.edu/abe_eng_pubs/1098
Comments
This is a manuscript of an article published as Shrestha, D. S., B. L. Steward, and S. J. Birrell. "Video processing for early stage maize plant detection." Biosystems engineering 89, no. 2 (2004): 119-129. DOI: 10.1016/j.biosystemseng.2004.06.007. Posted with permission.