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Open Access Top Down Approach to Height Histogram Estimation of Biomass Sorghum in the Field

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The rise of cheaper and more accurate genotyping techniques has lead to significant advances in understanding the genotype-phenotype map. However, this is currently bottlenecked by manually intensive or slow phenotype data collection. We propose an algorithm to automatically estimate the canopy height of a row of plants in field conditions in a single pass on a moving robot. A stereo sensor pointed down collects a series of stereo image pairs. The depth images are then converted to height-above-ground images to extract height contours. Separate height contours corresponding to each frame are then concatenated to construct a height contour representing one row of plants in the plot. Since the process is automated, data can be collected throughout the growing season with very little manual labor complementing the already abundantly available genotypic data. Using experimental data from seven plots, we show our proposed approach achieves a height estimation error of approximately 3.3%.
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Keywords: COMPUTER VISION; IMAGE PROCESSING; PHENOMICS; STEREO

Document Type: Research Article

Publication date: January 1, 2018

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

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