Perform morphological 'erosion' filtering. Keeps pixel in center of the kernel if conditions set in kernel are true, otherwise removes pixel.

plantcv.erode(gray_img, kernel, i)

returns image after erosion

  • Parameters:

    • gray_img - Grayscale (usually binary) image data
    • kernel - An odd integer that is used to build a kernel x kernel matrix using np.ones. Must be greater than 1 to have an effect
    • i - An integer for number of iterations, i.e. the number of consecutive filtering passes
  • Context:

    • Used to perform morphological erosion filtering. Helps remove isolated noise pixels or remove boundary of objects.
  • Example use:

Input grayscale 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 = "print"

# Perform erosion filtering
# Results in removal of isolated pixels or boundary of object removal
er_img = pcv.erode(gray_img, kernel, 1)

Image after erosion