Counting leaves without ``finger-counting'' by supervised multiscale frequency analysis of depth images from top view
Author(s) -
David Rousseau,
Henricus J. Van de Zedde
Publication year - 2015
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.29.cvppp.2
Subject(s) - computer science , artificial intelligence , computer vision , pattern recognition (psychology)
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.
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