Counting leaves without ``finger-counting'' by supervised multiscale frequency analysis of depth images from top view

David Rousseau and Henricus J. Van de Zedde

Abstract

Depth imaging is applied to characterize the shoot of seedlings from top-view. We demonstrate how quantitative informations of biological interest, such as leaves counting can be extracted from such images without performing 3D reconstruction of the shoot. This is obtained from 2D Fourier multiscale analysis without any requirement to segment nor detect leaves one by one numerically. We discuss the robustness and limitations of this approach and present possible extension with 3D Fourier analysis applied to estimate the plant plastochrone or 3D+T Fourier analysis in the estimation of circadian rythms.

Session

Workshop: Computer Vision Problems in Plant Phenotyping (CVPPP 2015)

Files

PDF iconPaper (PDF, 739K)

DOI

10.5244/C.29.CVPPP.2
https://dx.doi.org/10.5244/C.29.CVPPP.2

Citation

David Rousseau and Henricus J. Van de Zedde. Counting leaves without ``finger-counting'' by supervised multiscale frequency analysis of depth images from top view. In S. A. Tsaftaris, H. Scharr, and T. Pridmore, editors, Proceedings of the Computer Vision Problems in Plant Phenotyping (CVPPP), pages 2.1-2.9. BMVA Press, September 2015.

Bibtex

@inproceedings{CVPP2015_2,
	title={Counting leaves without ``finger-counting'' by  supervised multiscale frequency  analysis of depth images from top view},
	author={David Rousseau and Henricus J. Van de Zedde},
	year={2015},
	month={September},
	pages={2.1-2.9},
	articleno={2},
	numpages={9},
	booktitle={Proceedings of the Computer Vision Problems in Plant Phenotyping (CVPPP)},
	publisher={BMVA Press},
	editor={S. A. Tsaftaris, H. Scharr, and T. Pridmore},
	doi={10.5244/C.29.CVPPP.2},
	isbn={1-901725-55-3},
	url={https://dx.doi.org/10.5244/C.29.CVPPP.2}
}