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Modeling leaf growth of rosette plants using infrared stereo image sequences

AutorAksoy, Eren Erdal; Abramov, Alexey; Wörgötter, Florentin; Scharr, Hanno; Fischbach, Andreas; Dellen, Babette
Palabras claveLeaf segmentation
Leaf modeling
Plant growth
Leaf tracking
Fecha de publicación2015
CitaciónComputers and Electronics in Agriculture 110: 78-90 (2015)
ResumenIn this paper, we present a novel multi-level procedure for finding and tracking leaves of a rosette plant, in our case up to 3 weeks old tobacco plants, during early growth from infrared-image sequences. This allows measuring important plant parameters, e.g. leaf growth rates, in an automatic and non-invasive manner. The procedure consists of three main stages: preprocessing, leaf segmentation, and leaf tracking. Leaf-shape models are applied to improve leaf segmentation, and further used for measuring leaf sizes and handling occlusions. Leaves typically grow radially away from the stem, a property that is exploited in our method, reducing the dimensionality of the tracking task. We successfully tested the method on infrared image sequences showing the growth of tobacco-plant seedlings up to an age of about 30. days, which allows measuring relevant plant growth parameters such as leaf growth rate. By robustly fitting a suitably modified autocatalytic growth model to all growth curves from plants under the same treatment, average plant growth models could be derived. Future applications of the method include plant-growth monitoring for optimizing plant production in green houses or plant phenotyping for plant research.
Identificadoresdoi: 10.1016/j.compag.2014.10.020
issn: 0168-1699
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