Sauvola binarization

Description

Sauvola binarization: From skimage - Applies Sauvola local threshold to an array. Sauvola is a modification of Niblack technique.

In the original method a threshold T is calculated for every pixel in the image using the following formula:

T = m(x,y) _ (1 + k _ ((s(x,y) / R) - 1))
where m(x,y) and s(x,y) are the mean and standard deviation of pixel (x,y)
neighborhood defined by a rectangular window with size w times w centered around the pixel.
k is a configurable parameter that weights the effect of standard deviation. R is the maximum standard deviation
of a greyscale image.
Real time: True

Usage

• Threshold: Creates a mask that keeps only parts of the image

Parameters

• Channel (channel): (default: l)
• Invert mask (invert_mask): Invert result (default: 0)
• Window size (window_size): (default: 25)
• k threshold formula (k): (default: 20)
• Morphology operator (morph_op): (default: none)
• Kernel size (kernel_size): (default: 3)
• Kernel shape (kernel_shape): (default: ellipse)
• Iterations (proc_times): (default: 1)
• Overlay text on top of images (text_overlay): Draw description text on top of images (default: 0)

Example

Source

Parameters/Code

Default values are not needed when calling function

from ipapi.ipt import call_ipt

mask = call_ipt(ipt_id="IptSauvola",
                source="arabido_sample_plant.jpg",
                window_size=100,
                k=0,
                text_overlay=1)

Result