Find Branch/Junction Points¶

Find branch/junction points in a skeletonized image.

plantcv.morphology.find_branch_pts(skel_img, mask=None, label=None)

returns Binary mask of branch points

• Parameters:
  • skel_img - Skeleton image (output from plantcv.morphology.skeletonize)
  • mask - Binary mask used for debugging image (optional). If provided the debug image will be overlaid on the mask.
  • label - Optional label parameter, modifies the variable name of observations recorded. (default = pcv.params.sample_label)

• Context:

  • Identifies branch/junction points in a skeleton image

• Output data stored: Data ('branch_pts') automatically gets stored to the Outputs class when this function is ran. All data stored in the Outputs class gets printed out while running pcv.outputs.save_results but these data can always get accessed during a workflow. For more detail about data output see Summary of Output Observations

Skeleton Image

from plantcv import plantcv as pcv

# Set global debug behavior to None (default), "print" (to file), 
# or "plot" (Jupyter Notebooks or X11)
pcv.params.debug = "plot"
# Optionally, set a sample label name
pcv.params.sample_label = "plant"

branch_points_img = pcv.morphology.find_branch_pts(skel_img=skeleton)

# Adjust line thickness with the global line thickness parameter (default = 5),
# and provide binary mask of the plant for debugging. NOTE: the image returned
# will be exactly the same, but the debugging image will look different. 
pcv.params.line_thickness = 2

branch_points_img = pcv.morphology.find_branch_pts(skel_img=skeleton, mask=None)
branch_points_img = pcv.morphology.find_branch_pts(skel_img=skeleton, mask=plant_mask, label="rep1")

Branch Points Image (image getting returned)

Debug Image without Mask

Debug Image with Mask

Source Code: Here