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Related Concept Videos

Light Acquisition02:16

Light Acquisition

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
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[Segmentation of Winter Wheat Canopy Image Based on Visual Spectral and Random Forest Algorithm].

Ya-dong Liu, Ri-xian Cui

    Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
    |March 12, 2016
    PubMed
    Summary

    Digital image analysis effectively segments winter wheat plants from soil using random forest methods. This approach offers accurate crop monitoring without complex color transformations.

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    Area of Science:

    • Agricultural Science
    • Computer Vision
    • Remote Sensing

    Context:

    • Digital image analysis is crucial for non-destructive crop monitoring.
    • Accurate segmentation of winter wheat from soil is needed for analyzing canopy cover and spectral data.

    Purpose:

    • To evaluate segmentation methods for winter wheat from soil background.
    • To compare Otsu's method with RGB and CIEL*a*b* based random forest methods.

    Summary:

    • Three methods were tested: Otsu's on CIEL*a*b* a* component, and random forest on RGB and CIEL*a*b* color spaces.
    • All methods showed good segmentation ability, but random forest methods outperformed Otsu's.
    • Random forest methods achieved high accuracy using only visual spectral information.

    Impact:

    • The study highlights the effectiveness of random forest for precise crop segmentation.
    • This facilitates advanced analysis of crop growth and nitrogen status using digital imaging.