Homogenising and segmenting hyperspectral images of plants and testing chemicals in a high-throughput plant phenotyping setup

Mishra, Puneet and Schmuck, Martin and Roth, Sina and Nicol, Andreas and Nordon, Alison; (2019) Homogenising and segmenting hyperspectral images of plants and testing chemicals in a high-throughput plant phenotyping setup. In: 2019 10th Workshop on Hyperspectral Imaging and Signal Processing. IEEE, Piscataway. ISBN 9781728152943 (https://doi.org/10.1109/WHISPERS.2019.8921019)

[thumbnail of Mishra-etal-WHISPERS2019-Homogenising-and-segmenting-hyperspectral-images-of-plants-and-testing-chemicals]
Preview
 Text. Filename: Mishra_etal_WHISPERS2019_Homogenising_and_segmenting_hyperspectral_images_of_plants_and_testing_chemicals.pdf
Accepted Author Manuscript
Download (403kB)| Preview

Abstract

Use of hyperspectral imaging (HSI) for automated characterisation of plants in a high-throughput plant phenotyping setup (HTPPS) is a challenging task. A challenge arises when the same plant is being monitored automatically during the experiment as it might not be in the same orientation as it was imaged last time. Such changes in orientation result in variations in illumination, which affects the signals recorded by the HSI setup. In addition, there are challenges with the use of threshold-based segmentation approaches such as normalised difference vegetation index (NDVI) for distinguishing between old and dead leaves, which might be observed in the later stages of experiments, from the soil background. Therefore, the potential of spectral normalisation for homogenising HS images and the use of supervised spectral set for plant segmentation is presented. Further, the effects of testing chemicals on plants were visualised using PCA of the HS images.

ORCID iDs

Mishra, Puneet, Schmuck, Martin, Roth, Sina, Nicol, Andreas and Nordon, Alison ORCID logoORCID: https://orcid.org/0000-0001-6553-8993;
CORE (COnnecting REpositories)