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000186416 1001_ $$0P:(DE-HGF)0$$aAksoy, Eren Erdal$$b0$$eCorresponding Author
000186416 245__ $$aModeling leaf growth of rosette plants using infrared stereo image sequences
000186416 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2015
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000186416 520__ $$aIn this paper, we present a novel multi-level procedure for finding and tracking leaves of a rosette plant, in our case up to 3 weeks old tobacco plants, during early growth from infrared-image sequences. This allows measuring important plant parameters, e.g. leaf growth rates, in an automatic and non-invasive manner. The procedure consists of three main stages: preprocessing, leaf segmentation, and leaf tracking. Leaf-shape models are applied to improve leaf segmentation, and further used for measuring leaf sizes and handling occlusions. Leaves typically grow radially away from the stem, a property that is exploited in our method, reducing the dimensionality of the tracking task. We successfully tested the method on infrared image sequences showing the growth of tobacco-plant seedlings up to an age of about 30 days, which allows measuring relevant plant growth parameters such as leaf growth rate. By robustly fitting a suitably modified autocatalytic growth model to all growth curves from plants under the same treatment, average plant growth models could be derived. Future applications of the method include plant-growth monitoring for optimizing plant production in green houses or plant phenotyping for plant research.
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000186416 7001_ $$0P:(DE-HGF)0$$aAbramov, Alexey$$b1
000186416 7001_ $$0P:(DE-HGF)0$$aWörgötter, Florentin$$b2
000186416 7001_ $$0P:(DE-Juel1)129394$$aScharr, Hanno$$b3$$ufzj
000186416 7001_ $$0P:(DE-Juel1)129315$$aFischbach, Andreas$$b4$$ufzj
000186416 7001_ $$0P:(DE-HGF)0$$aDellen, Babette$$b5
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