Laplace Filter

This is a filtering method used to identify and highlight fine edges based on the 2nd derivative.

plantcv.laplace_filter(gray_img, ksize, scale)

returns filtered image

  • Parameters:

    • gray_img - Grayscale image data
    • ksize - apertures size used to calculate 2nd derivative filter, specifies the size of the kernel (must be an odd integer: 1,3,5...)
    • scale - scaling factor applied (multiplied) to computed Laplacian values (scale = 1 is unscaled)

  • Context:

    • Used to define edges around objects
  • Example use:
    • Below

Input grayscale image

Screenshot

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 to a grayscale image
# Filtered image will highlight areas of rapid pixel intensity change
lp_img = pcv.laplace_filter(gray_img=gray_img, ksize=1, scale=1)

Image after Laplace filter

Screenshot

Source Code: Here