Figure 3.

The workflow of the proposed image-processing pipeline. Images shown are based on the example application to a maize data set (for summary of the data set, see Table I). Image data and metadata are imported via IAP functionalities (top) and subjected to image processing, including (1) preprocessing, prepare the images for segmentation; (2) segmentation, divide the image into different parts that have different meanings (foreground, plant; background, imaging chamber and machinery); (3) feature extraction, classify the segmentation result and get a trait list (examples include images from visible-light, fluorescence, and near-infrared [NIR] cameras); and (4) postprocessing, summarize calculated results for each plant. Optionally, analysis results can be marked in the images. Finally, result images are exported. Numbers in parentheses indicate the percentage of overall processing time for each analysis step.