Issue with morphological filters

Fri Mar 27 11:32:39 EDT 2015

Hello Juan

Here it is: 
http://nbviewer.ipython.org/urls/dl.dropbox.com/s/ancfxe2gx1fbyyp/morphology_test.ipynb?dl=0
I get the same, odd results, with both ndimage's binary_fill_holes, and 
reconstruction. IS it because of the structuring elements/masks?
Thanks for your help.
Matteo

On Thursday, March 26, 2015 at 11:14:05 PM UTC-6, Juan Nunez-Iglesias wrote:

> Hi Matteo,
>
> Can you try putting this notebook up as a gist and pasting a link to the 
> notebook? It's hard for me to follow all of the steps (and the polarity of 
> the image) without the images inline. Is it just the inverse of what you 
> want? And anyway why aren't you just using ndimage's binary_fill_holes?
>
>  
> https://docs.scipy.org/doc/scipy-0.15.1/reference/generated/scipy.ndimage.morphology.binary_fill_holes.html
>
> Juan.
>  
>
>
>
> On Fri, Mar 27, 2015 at 9:09 AM, Matteo <matteo.... at gmail.com 
> <javascript:>> wrote:
>
>  Hello Juan
>
> Thanks so much for your suggestions.
> Once I convertedthe image as you suggested:
>  # import back image
> cfthdr=io.imread('filled_contour_THDR.png')
> cfthdr = color.rgb2gray(cfthdr) > 0.5 
>
> I get good results with opening:
>  # clean it up with opening
> selem17 = disk(17)
> opened_thdr = opening(cfthdr, selem17)/255
> # plot it 
> fig = plt.figure(figsize=(5, 5))
> ax = fig.add_subplot(1, 1, 1)
> ax.set_xticks([])
> ax.set_yticks([])
> plt.imshow(opened_thdr,cmap='bone')
> plt.show()
> # not bad
>  
>
> With remove_small_objects the advantage is that it does not join blobs in 
> the original:
>  cfthdr_inv = ~cfthdr
> test=remove_small_objects(cfthdr,10000)
> # plot it 
> fig = plt.figure(figsize=(5, 5))
> ax = fig.add_subplot(1, 1, 1)
> ax.set_xticks([])
> ax.set_yticks([])
> plt.imshow(test,cmap='bone')
> plt.show() 
>
>
> but with reconstruction done as this:
>  # filling holes with morphological reconstruction
> seed = np.copy(cfthdr_inv)
> seed[1:-1, 1:-1] = cfthdr_inv.max()
> mask = cfthdr_inv
> filled = reconstruction(seed, mask, method='erosion')
> # plot it 
> fig = plt.figure(figsize=(5, 5))
> ax = fig.add_subplot(1, 1, 1)
> ax.set_xticks([])
> ax.set_yticks([])
> plt.imshow(filled,cmap='bone',vmin=cfthdr_inv.min(), vmax=cfthdr_inv.max
> ())
> plt.show() 
>  
> I get a completely white image. Do you have any suggestions as to why?
>
> Thank again. Cheers,
> Matteo
>
>  
> On Wednesday, March 25, 2015 at 6:29:43 PM UTC-6, Juan Nunez-Iglesias 
> wrote:
>
> Hi Matteo,
>
> My guess is that even though you are looking at a "black and white" image, 
> the png is actually an RGB png. Just check the output of 
> "print(cfthdr.shape)". Should be straightforward to make it a binary image:
>
> from skimage import color
>  cfthdr = color.rgb2gray(cfthdr) > 0.5
>
> Then you should have a binary image. (And inverting should be as simple as 
> "cfthdr_inv = ~cfthdr") We have morphology.binary_fill_holes to do what you 
> want.
>
> btw, there's also morphology.remove_small_objects, which does exactly what 
> you did but as a function call. Finally, it looks like you are not using 
> the latest version of scikit-image (0.11), so you might want to upgrade.
>
> Hope that helps!
>
> Juan.
>  
>
>
>
> On Thu, Mar 26, 2015 at 8:48 AM, Matteo <matteo.... at gmail.com> wrote:
>
>   *Issues with morphological filters when trying to remove white holes in 
> black objects in a binary images. Using opening or filling holes on 
> inverted (or complement) of the original binary.*
>
> Hi there 
>  
> I have a series of derivatives calculated on geophysical data.
>  
> Many of these derivatives have nice continuous maxima, so I treat them as 
> images on which I do some cleanup with morphological filter. 
>  
> Here's one example of operations that I do routinely, and successfully:
>  
> # threshold theta map  using Otsu method
>  
> thresh_th = threshold_otsu(theta)
>  
> binary_th = theta > thresh_th
>  
> # clean up small objects
>  
> label_objects_th, nb_labels_th = sp.ndimage.label(binary_th)
>  
> sizes_th = np.bincount(label_objects_th.ravel())
>  
> mask_sizes_th = sizes_th > 175
>  
> mask_sizes_th[0] = 0
>  
> binary_cleaned_th = mask_sizes_th[label_objects_th]
>  
> # further enhance with morphological closing (dilation followed by an 
> erosion) to remove small dark spots and connect small bright cracks
>  
> # followed by an extra erosion
>  
> selem = disk(1)
>  
> closed_th = closing(binary_cleaned_th, selem)/255
>  
> eroded_th = erosion(closed_th, selem)/255
>  
> # Finally, extract lienaments using skeletonization
>  
> skeleton_th=skeletonize(binary_th)
>  
> skeleton_cleaned_th=skeletonize(binary_cleaned_th)
>  
> # plot to compare
>  
> fig = plt.figure(figsize=(20, 7))
>  
> ax = fig.add_subplot(1, 2, 1)
>  
> imshow(skeleton_th, cmap='bone_r', interpolation='none')
>  
> ax2 = fig.add_subplot(1, 3, 2)
>  
> imshow(skeleton_cleaned_th, cmap='bone_r', interpolation='none')
>  
> ax.set_xticks([])
>  
> ax.set_yticks([])
>  
> ax2.set_xticks([])
>  ax2.set_yticks([])
>
>  Unfortunately I cannot share the data as it is proprietary, but I will 
> for the next example, which is the one that does not work.
>
>  There's one derivative that shows lots of detail but not continuous 
> maxima. As a workaround I created filled contours in Matplotlib
>  
> exported as an image. The image is attached.
>  
> Now I want to import back the image and plot it to test: 
>  
> # import back image 
>  
> cfthdr=io.imread('filled_contour.png') 
>  
> # threshold using using Otsu method 
>  
> thresh_thdr = threshold_otsu(cfthdr) 
>  
> binary_thdr = cfthdr > thresh_thdr 
>  
> # plot it 
>  
> fig = plt.figure(figsize=(5, 5)) 
>  
> ax = fig.add_subplot(1, 1, 1) 
>  
> ax.set_xticks([]) 
>  
> ax.set_yticks([]) 
>  
> plt.imshow(binary_thdr, cmap='bone') 
>  
> plt.show() 
>  
> The above works without issues. 
>  
>  
>  
> Next I want to fill the white holes inside the black blobs. I thought of 2 
> strategies.
>  
> The first would be to use opening; the second to invert the image, and 
> then fill the holes as in here: 
>  
> http://scikit-image.org/docs/dev/auto_examples/plot_holes_and_peaks.html 
>  
> By the way, I found a similar example for opencv here
>  
>
> http://stackoverflow.com/questions/10316057/filling-holes-inside-a-binary-object
>   
> Let's start with opening. When I try: 
>  
> selem = disk(1) 
>  
> opened_thdr = opening(binary_thdr, selem) 
>  
> or:
>  
> selem = disk(1) 
>  
> opened_thdr = opening(cfthdr, selem) 
>  
> I get an error message like this: 
>  
> --------------------------------------------------------------------------- 
>
>  
> ValueError                                Traceback (most recent call 
> last) 
>  
> <ipython-input-49-edc0d01ba327> in <module>() 
>  
>       1 #binary_thdr=img_as_float(binary_thdr,force_copy=False) 
>  
> ----> 2 opened_thdr = opening(binary_thdr, selem)/255 
>  
>       3 
>
> ...

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