Apply segmentation to a large binary image

[Josh Warner]

Would it be possible to generalize / refactor `clear_border` to a function 
which removes all points connected to a specific pixel/voxel? That would 
greatly simplify the work needed here.

I thought we had some sort of `remove_object` functionality like this, but 
I don't see it.

Josh

On Friday, March 13, 2015 at 9:04:12 PM UTC-5, Juan Nunez-Iglesias wrote:
>
> Hey Yuta,
>
> You'll need to do some stitching out-of-core. That's a really tricky 
> problem and I don't have any ready-made solutions for you. The solution 
> will depend on the nature of your segments. The only thing I would 
> recommend is that you use a format such as HDF5 (you can use the excellent 
> h5py library) that allows random access into the underlying disk data.
>
> Other than that, as I said, to my knowledge you'll have to develop your 
> own stitching: segment *overlapping* tiles independently in memory, and 
> when it comes time to write to disk, load the tile and overlapping tiles 
> that have already been segmented, and resolve label mapping then...
>
> Generally, think of it this way: tile i has already been segmented and 
> written out. We now want to write out tile j, which overlaps tile i. Labels 
> from tile i that intersect labels from tile j in the overlap region should 
> be matched. labels in tile j that *don't* intersect tile i should be 
> relabelled to ensure they are unique with respect to tile i.
>
> Of course this gets a bit more complicated in 2D or 3D...
>
> Juan.
>
>
>
>
> On Fri, Mar 13, 2015 at 7:20 PM, Yuta Sato <yutaxsato at gmail.com> wrote:
>
>>  Dear SKIMAGE Developers and Users:
>>
>> I want to use the following algorithm in a large binary image that does 
>> not fit into my PC memory. So, I am thinking to split my large image into 
>> tiles and apply algorithm one by one. However, the original border 
>> definition change when I do it in parts. I need the result as applied in 
>> original full image. How can I do it efficiently?
>>
>> skimage.segmentation.clear_border(image, buffer_size=0, bgval=0)
>>
>> Thanks for your ideas.
>>  
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>
>
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