Image segementation of cement paste complex structure!

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xsfeng 2013-12-9

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评论： Image Analyst 2019-4-6

Dear all,

I have a cement paste gray image of the CT, now I want to do some quantative analysis of the porosity and the microstructure characterization. From the image we at least can get 4 main composition, how can I use the histogram or threshold to finely distinguish different parts in this image? Can anybody help me with the Matlab programming? I tried the standard segmentation but it doesn´t work so well since the boundary of cement material is almost invisible. Thank you so much for your help.

Joanna

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Maria Huguett 2019-4-5

Could you tell me please, where can I find the "Sean's intensity thresholding method"? I would like to try it, since I need a method to segmentate pores, grains and paraffin of my sediment sample, to get porosity values. Thanks!

Image Analyst 2019-4-6

Maria, it's in Sean's answer below. Click here to scroll down to it.

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Image Analyst 2013-12-9

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I'm not sure what you meant by "the boundary of cement material is almost invisible" - perhaps you could explain.

If Sean's intensity thresholding method doesn't work, like say you had some structures that were of the same brightness but just different textures, you could combine that with some texture segmentation. Try stdfilt() or entropyfilt(). Or you could try simulated annealing (I have a demo fro that if you want). Again, only for cases where intensity thresholding doesn't do the job well enough.

If you want an intensity thresholding segmentation demo, see my Image Segmentation Tutorial: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862

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xsfeng 2013-12-13

Yep, we have both flat field and dark field and for the reconstruction we use filtered back projection algorithm. But the imaging principle is the same as the conventional CT.

Sean de Wolski 2013-12-13

I guess I'm having a hard time understanding why there isn't more contrast and why the background (air) isn't the darkest part...

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Sean de Wolski 2013-12-9

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https://ww2.mathworks.cn/matlabcentral/answers/109183-image-segementation-of-cement-paste-complex-structure#answer_117826

编辑：Sean de Wolski 2013-12-9

在 MATLAB Online 中打开

There are a few things a little weird about your image:

First, for a CT image, I'd expect the background to have a lower intensity than everything else since this is void space (unless is was scanned in a liquid of some kind). What do you know about the setup of the system and do you have control over it?
Second, it appears the histogram has already been modified in some way. I would expect this to be fairly bimodal for an object in the forground.

As far as identifying the cement matrix, here's a rough first pass to get you started:

I = imread('cct.jpg');

mask of the concrete part

disk = getnhood(strel('disk',4)); %disk
Istd = stdfilt(I,disk); %std filter tor emove backgoryund
Mcyl = Istd>2;
C = (conv2(double(I),double(disk),'same'));
levels = multithresh(C,2); %otsu thresholding
L = imquantize(C,levels); %apply thresholds
L = L+1; %increment
L(~Mcyl) = 0; %remove background
%%visualize
cmap = [1 1 1;lines(3)]; % colormap
Lrgb = label2rgb(L,cmap); % to view
% view it
imshow(Lrgb);
colormap(cmap);
hCb = colorbar;
set(hCb,'YTick',0:3);
set(hCb,'YTickLabel',{'Background','Porous','Cement Matrix','Aggregate'});

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xsfeng 2013-12-9

Dear Sean,

Thanks so much for your quick guide! And I would like to answer your two questions: 1) This is one slice cross-section of 3D CT reconstruction of the cement cylinder sample. The background is the air with a gray value around 118, and the sample has no sealing or other environment to embedded during the scanning. 2) This is the .jpg image transferred from the original 16bits tiff file in order to upload, I didn´t make any change about the intensity or other information. If I understand your point correctly, there should have some peaks or multi-modal of the intensity to indicate the four main composition like: pores, HP, CH and AH, right? I think because this is a modified blending sample so the pores peak and the CH, AH ṕeak is too trivial in this histogram. And here is my continuous question about the imaging processing: 1) I would like to have statistic analysis about the main composition, so I want to get the volume of the pores, the aggregates, the hydration products and the undryated phases. Is that possible? 2) With simple threshold segmentation we can get roughly distinguished about the different parts, is it possible to have some precise and segmentation about the holes and the other parts? And then with the calculation of the volume?

Many thanks in advance!

Joanna

Sean de Wolski 2015-3-5

A morphological opening ( imopen) with a small structuring element should do it. Alternatively, you could create a mask of the pores and then use imfill(pores,'holes') to fill in all of the holes inside a pore.