Non-linear distance based filter

[Josh Warner]

Hi Eduardo,

What you are looking for is called a *distance transform*. We have one 
function (skimage.morphology.medial_axis) which can be coerced into 
returning a distance transform with an optional argument, but I recommend 
you look to SciPy’s NDImage module (scipy.ndimage) for a more general set 
of transforms. We haven’t reimplemented these since we depend on SciPy.

Specifically, for your purposes, you will likely want to use 
scipy.ndimage.distance_transform_edt and then either mask or threshold the 
result.

import scipy.ndimage as ndi
# Load your data here as `image`

dist = ndi.distance_transform_edt(image)
dist[dist < T] = 0  # Could also operate on the original image with image[dist < T] = something
# Optional, uncomment if you want a binary result# dist[dist >= T] = 1

Hope that helps,
Josh

On Tuesday, July 15, 2014 6:28:21 AM UTC-5, Eduardo Henrique Arnold wrote:

Hi there.
>
> I need to implement a filter that takes each white pixel in a binary image 
> and look for the distance between the top and bottom closest 
> background (black) pixels. If this distance is smaller than a threshold T 
> all the pixels between this two background pixels should be set to 0 
> (background pixels).
>
> I know I could iterate through all the image columns and pixels, but I 
> think this would yield a poor performance. Is there any suggestion of how I 
> could develop this filter in a more efficient way?
>
> Thanks.
>
​
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