@stefanv Yes, I'm reading up on some material by which I could have a better and more memory efficient algorithm for flood fill. I'm definitely interested in this. On Mon, Apr 22, 2013 at 6:02 PM, Stéfan van der Walt <stefan@sun.ac.za>wrote:

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It's very convenient to have direct access back to the pixels/voxels making up each superpixel. Therefore, I stored on each node an array containing all the linear indices into the `ravel`ed version of the image. This is

On Mon, Apr 22, 2013 at 11:55 AM, Juan Nunez-Iglesias <jni.soma@gmail.com> wrote: pretty

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expensive, though, so if could do it over, I would store the index of a single pixel belonging to that superpixel and pair it with a flood fill algorithm, so that a function `g.get_pixel_indices(superpixel_id)` would transparently return the pixel list, but in O(superpixel_size) time while only using up a singe int of space.

Thanks for sharing that good advice. Juan. There is also an intermediary storage format, one that I used before with some success. Think of a 2-D example: you store the start and end indices of each column that comprises the object, paired with an index into the rows (very similar to CSR). Perhaps it will be a bit painful to extend to N-d, but it is doable.

Another option is to store a graph in an array. This goes along very well with the implementation of ``graph.label``. At each position in the array, you store the index of the previous pixel to which it is connected. For any super-pixel, you can then store only the last pixel, and traverse indices backward to get the entire super-pixel. Con: 2 x storage.

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Related note: does skimage have an nd implementation of flood fill?

I think one of the recent PRs made an attempt at a 2D version called ``connected_component``, but otherwise no.

Stéfan

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