Issue with morphological filters

Thu Apr 2 09:22:03 EDT 2015

OK
Thanks so much for your efforts Juan, I will take a look. 
Matteo

On Sunday, March 29, 2015 at 10:03:23 PM UTC-6, Juan Nunez-Iglesias wrote:

> Hmm, I must say I don't know what's going on with either the 
> reconstruction or the binary_fill_holes. (Originally I thought the image 
> was inverted but you tried both polarities...) My advice would be to look 
> at a few iterations of morphological reconstruction manually and see what's 
> going on...
>
> Also, I would use the "grey" colormap, which is the most intuitive to look 
> at (you used a reversed colormap for a couple of the images).
>
> Finally, it may be that you need to fill each "blob" independently. If so, 
> have a look at skimage.measure.regionprops.filled_image.
>  http://scikit-image.org/docs/dev/api/skimage.measure.html#regionprops
>
> Juan.
>  
>
>
>
> On Sat, Mar 28, 2015 at 2:32 AM, Matteo <matteo.... at gmail.com 
> <javascript:>> wrote:
>
>>  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> 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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