Modeling leaf growth of rosette plants using infrared stereo image sequences

Journal Article (2015)


Computers and Electronics in Agriculture





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  • Aksoy, Eren Erdal

  • Abramov, Alexey

  • Wörgötter, Florentin

  • Scharr, Hanno

  • Fischbach, Andreas

  • Dellen, Babette

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In 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.


computer vision.

Author keywords

Leaf segmentation; Leaf tracking; Leaf modeling; Plant growth; Phenotyping

Scientific reference

E.E. Aksoy, A. Abramov, F. Wörgötter, H. Scharr, A. Fischbach and B. Dellen. Modeling leaf growth of rosette plants using infrared stereo image sequences. Computers and Electronics in Agriculture, 110: 78-90, 2015.