Closing

Filters out dark noise from an image.

plantcv.closing(gray_img, kernel=None, roi=None)

returns filtered_img

  • Parameters:
    • gray_img - Grayscale or binary image data
    • kernel - Optional neighborhood, expressed as an array of 1's and 0's. See the kernel making function. If None, use cross-shaped structuring element.
    • roi - Optional rectangular ROI as returned by pcv.roi.rectangle within which to apply this function. (default = None, which uses the entire image)
  • Context:
    • Used to reduce image noise, specifically small dark spots (i.e. "pepper").
  • Example use:
    • See below

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"

# Apply closing
filtered_img = pcv.closing(gray_img=gray_img)

Grayscale image

Screenshot

Closing

Screenshot

In addition to the kernel making function users can create custom kernel shapes. 


# Apply closing with an X-shaped kernel 
filtered_img = pcv.closing(gray_img=gray_img, kernel=np.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]]))

Source Code: Here