Non-linear distance based filter

[Eduardo Henrique Arnold]

Hi Josh, 

I appreciate your reply, it was very helpful. Looking at the Scipy docs 
<http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.morphology.distance_transform_edt.html#scipy.ndimage.morphology.distance_transform_edt>, 
I've realized I could use the *sampling* argument to get only vertical 
distances. However this does not seem to work, it shows me an empty matrix 
no matter what. If I invert the order of the sampling list, [1,0], it shows 
me some line strips, but not the result I was expecting. I cannot figure 
out what is wrong or if this method is not supposed be used like this.

from scipy.ndimage.morphology import distance_transform_edt as distTransform

distMatrix = distTransform(imgBin, sampling=[0,1])


BTW, did you format your code in the last post manually? I could not find a 
way of doing it here. 

Thanks again!

On Tuesday, July 15, 2014 1:03:04 PM UTC+1, Josh Warner wrote:
>
> 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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