This is a filtering method used to identify and highlight coarse changes in pixel intensity based on the 1st derivative.
sobel_filter(img, dx,dy,k, device, debug=None)
returns device, filtered image
- img - binary image object. This image will be returned after filling.
- dx - derivative of x to analyze (0-3)
- dy - derivative of y to analyze (0-3)
- k - apertures size used to calculate 2nd derivative filter, specifies the size of the kernel (must be an odd integer: 1,3,5...)
- device - Counter for image processing steps
- debug - None, "print", or "plot". Print = save to file, Plot = print to screen. Default = None
- Used to define edges within and around objects
- Example use:
Original grayscale image
from plantcv import plantcv as pcv # Apply to a grayscale image # Filtered image will highlight areas of coarse pixel intensity change based on 1st derivative device, lp_img = pcv.sobel_filter(img, 1, 0, 1, device, debug="print") device, lp_img = pcv.sobel_filter(img, 0, 1, 1, device, debug="print")
Sobel filtered (x-axis)
Sobel filtered (y-axis)