how to Identify the centre of atom

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玥 2024-4-12

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2105946-how-to-identify-the-centre-of-atom

评论： DGM 2024-4-13

采纳的回答： DGM

how to Identify the centre of gravity like the fllowing figure

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Answer 1

DGM 2024-4-12

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https://ww2.mathworks.cn/matlabcentral/answers/2105946-how-to-identify-the-centre-of-atom#answer_1440256

在 MATLAB Online 中打开

image.png

Here's a start.

% the original image

inpict = imread('image.png');

inpict = im2gray(inpict);

% crop out the subimages

A0 = imcrop(inpict,[31.51 30.51 277.98 277.98]);

B0 = imcrop(inpict,[326.51 30.51 277.98 277.98]);

C0 = imcrop(inpict,[621.51 30.51 277.98 277.98]);

% process A

A = imflatfield(A0,10);

A = adapthisteq(A);

A = imopen(A,strel('disk',3,0));

maskA = imextendedmax(A,50); % roughly get a mask of minimal regions

maskA = imclearborder(maskA); % get rid of partial blobs

imshow(maskA,'border','tight')

% process B

maskB = imextendedmin(B0,80); % roughly get a mask of minimal regions

maskB = imclearborder(maskB); % get rid of partial blobs

imshow(maskB,'border','tight')

% process C

C = imflatfield(C0,10);

C = adapthisteq(C);

maskC = imextendedmin(C,80); % roughly get a mask of minimal regions

maskC = imclearborder(maskC); % get rid of partial blobs

imshow(maskC,'border','tight')

% for example, find the centroids of the blobs in one of the masks

Sc = regionprops(maskC,'centroid');

centers = vertcat(Sc.Centroid);

% mark the centers on the mask

hold on;

plot(centers(:,1),centers(:,2),'x','linewidth',2)

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DGM 2024-4-13

编辑：DGM 2024-4-13

在 MATLAB Online 中打开

image2.png

Hm. Well. I threw some time at just using blob properties to sort out the masks. It's obviously not very consistent, but a fair bit of it is correct. Maybe @Image Analyst has some ideas about how this sort of things could be classified, but I'm not really satisfied with where my attempt is going.

% the original image

inpict = imread('image2.png');

inpict = im2gray(inpict);

% crop off the border remants

inpict = imcrop(inpict,[3.51 2.51 222.98 223.98]);

% upsample so our property measurements aren't so distorted by the resolution

inpict = imresize(inpict,2);

% stretch contrast

inpict = imadjust(inpict);

% create masks of local extrema

minex = 40;

maskmx = imextendedmax(inpict,minex);

maskmn = imextendedmin(inpict,minex);

% get rid of partial blobs on the border

maskmx = imclearborder(maskmx);

maskmn = imclearborder(maskmn);

% try to filter out some blobs based on their properties

% this is probably something that could also be done with bwpropfilt()

% or using cc2bw(), but i'm using R2019b, where that's not an option.

minc = 0.9; % minimum circularity

maxecc = 0.8; % maximum eccentricity

minarea = 100; % minimum area

Lmx = bwlabel(maskmx);

Smx = regionprops(maskmx,'circularity','eccentricity','area');

goodblobs = find([Smx.Circularity] >= minc ...

& [Smx.Eccentricity] <= maxecc ...

& [Smx.Area] >= minarea);

maskmx = any(Lmx == permute(goodblobs,[1 3 2]),3);

Lmn = bwlabel(maskmn);

Smn = regionprops(maskmn,'circularity','eccentricity','area');

goodblobs = find([Smn.Circularity] >= minc ...

& [Smn.Eccentricity] <= maxecc ...

& [Smn.Area] >= minarea);

maskmn = any(Lmn == permute(goodblobs,[1 3 2]),3);

% visualize the masks and the image by concatenation

outpict = cat(3,im2uint8(maskmx),im2uint8(maskmn),inpict);

imshow(outpict,'border','tight')

Dark features are marked in green, light features are in purple. The blue channel is the original image.

Image Analyst 2024-4-13

@DGM in your first response, since he specifically wanted the center of gravity, you should have used "WeightedCentroid" instead of 'Centroid', though for this image it looks like they should be really close to the same location.

Maybe, after field flattening, you can use kmeans to classify a pixel as light, dark, or gray.

DGM 2024-4-13

在 MATLAB Online 中打开

image.png

That's a pretty good point. I'll throw in an example just for sake of completeness.

% the original image

inpict = imread('image.png');

inpict = im2gray(inpict);

% crop out the subimages (i'm just going to use C)

C0 = imcrop(inpict,[621.51 30.51 277.98 277.98]);

% process C (same as before)

C = imflatfield(C0,10);

C = adapthisteq(C);

maskC = imextendedmin(C,80); % roughly get a mask of minimal regions

maskC = imclearborder(maskC); % get rid of partial blobs

% for example, find the weighted centroids of the blobs in one of the masks

% in this call to regionprops, it's important to make sure that the second argument

% has a light-on-dark polarity, hence the use of imcomplement() in the case of B or C.

% A is already light-on-dark, so we wouldn't need to complement it.

Sc = regionprops(maskC,imcomplement(C),'weightedcentroid');

centers = vertcat(Sc.WeightedCentroid);

imshow(maskC,'border','tight'); hold on;

plot(centers(:,1),centers(:,2),'x','linewidth',2)

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how to Identify the centre of atom

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