Presentation
18 June 2024 Combined structural and functional 3D structure from motion plant imaging for the studying plant-pathogen interaction
Alim Yolalmaz, Jeroen Kalkman
Author Affiliations +
Abstract
Non-invasive, automated, and continuous 3D plant imaging is important for studying plant development, performing digital phenotyping, and detection of plant diseases. In this study, we reconstructed 3D plant structural and fluorescence plant images using an automated monocular vision-based structure from motion technique requiring only 2 RGB images. By using different exposure durations and RGB spectral filters we are able to acquire both white light structural information and fluorescence functional information in a single acquisition. The combined structural and function information enables us to observe and locate the plant disease of autofluorescing downy mildew lettuce plants in 3D. We demonstrate the effect of important parameters such as exposure duration and sampling frequency on the 3D reconstruction quality. We believe that our work will enable plant biologists and plant breeders to aid in understanding plant-pathogen interactions, plant development, and to utilize this for breeding more disease resistant crops.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Alim Yolalmaz and Jeroen Kalkman "Combined structural and functional 3D structure from motion plant imaging for the studying plant-pathogen interaction", Proc. SPIE 12998, Optics, Photonics, and Digital Technologies for Imaging Applications VIII, 129980Z (18 June 2024); https://doi.org/10.1117/12.3011252
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KEYWORDS
3D image processing

Biological imaging

Diseases and disorders

3D acquisition

Fluorescence

RGB color model

3D modeling

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