Within-row spacing sensing of maize plants using 3D computer vision

Date
2014-09-01
Authors
Nakarmi, Akash
Tang, Lie
Tang, Lie
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Tang, Lie
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Abstract

Within-row plant spacing plays an important role in uniform distribution of water and nutrients among plants which affects the final crop yield. While manual in-field measurements of within-row plant spacing is time and labour intensive, little work has been done on an alternative automated process. We have attempted to develop an automatic system making use of a state-of-the-art 3D vision sensor that accurately measures within-row maize plant spacing. Misidentification of plants caused by low hanging canopies and doubles were reduced by processing multiple consecutive images at a time and selecting the best inter-plant distance calculated. Based on several small scale experiments in real fields, our system has been proven to measure the within-row maize plant spacing with a mean and standard deviation error of 1.60 cm and 2.19 cm, and a root mean squared error of 2.54 cm, respectively.

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<p>This is a manuscript of an article published as Nakarmi, Akash D., and Lie Tang. "Within-row spacing sensing of maize plants using 3D computer vision." <em>Biosystems Engineering</em> 125 (2014): 54-64. DOI: <a href="http://dx.doi.org/10.1016/j.biosystemseng.2014.07.001" target="_blank">10.1016/j.biosystemseng.2014.07.001</a>. Posted with permission.</p>
Keywords
Spacing sensing, Inter-plant spacing, Within-row, 3D computer vision, Time-of-flight
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