number of disks in a grey scale Image

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ramin bba 2014-4-9

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编辑： ramin bba 2014-4-13

I am trying to find the number of black disks in this Image. I have tried "regionprops" but the problem is first I need to convert the Image to a binary one (without significant loss in resolution or accuracy) and then use this function. In addition, "regionprops" cannot distinguish "touching disks" quite well. I am using R2014a version.

Any help or comment would be greatly appreciated. Bests, Ramin

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Answer 1

Image Analyst 2014-4-9

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For an image like this, where all the blobs are very close to the same size, you simply threshold to find the entire mass and then divide by the area of a single blob. For all intents and purposes this will give you a very accurate count. There are other methods such as bwulterode() or Marker Controlled Watershed Segmentation but I think they may not be as accurate and are more complicated.

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ramin bba 2014-4-9

在 MATLAB Online 中打开

tnx,

That method definitely works. However, I do need to find the center of each of the disks because this image actually shows the cross sectional view of "fibers" (which is like a disk) within a composite and I need to investigate the distribution of the fibers in the third dimension(into the plane). In other words, I have several pictures (like this) which are taken from a 3D structure in different cross sections. To investigate the distribution, I want to simplify the problem by replacing each fiber with its center line (I am assuming that all the fibers have approximately the same radius and that the radius remains constant in the third dimension). Once I have the centers (corresponding to each fiber), I can fit a Spline to them to find the center line.

I wanted to use this code for "Filtering, adjusting (the contrast), and binarizing" the image and then using the "regionprops" command but I cannot get it to work this time:

background = medfilt2( Image, [20, 20] );

Image = double(Image) - double(background);

[~, Image] = transform(Image, 1-VF); %VF=Volume Fraction

Image = Image/255; %1=fiber

-------------------------------

function [iThreshold, BinaryImage] = transform(filepath, VF)

% Transform the grey images to binary images

% Input: filepath - a path of the grey *.tif SEM image OR

% a matrix with 0-255 grey level

% VF - volume fraction of the composite

% Output: iThreshold - threshold used to convert the image

% BinaryImage - the binary image

if ischar(filepath)

Img = imread(filepath);

else

    Img = 255-filepath;
end

Img = medfilt2(Img);

[row col] = size(Img);

TotalNopixel = row*col;

ThresholdPixelNo = ceil(TotalNopixel*VF);

ranking = sort(Img(:),'descend');

iThreshold = ranking(ThresholdPixelNo);

BinaryImage = zeros(row,col);

for i=1:row

    for j=1:col
        if  Img(i,j)>=iThreshold
            BinaryImage(i,j) = 0;
        else
            BinaryImage(i,j) = 255;
        end      
    end

end

% BinaryImage = uint8(BinaryImage);

% BinaryImage = double(BinaryImage);

% BinaryImage = abs(BinaryImage-255);

-----------------------------------------------

Thanks again,

Sincerely Yours'

Ramin

ramin bba 2014-4-11

Just took a look at the file. It is awesome! thanks a lot.

I will try to use my image as the input. Hope it works.

regards, Ramin

ramin bba 2014-4-12

编辑：ramin bba 2014-4-13

在 MATLAB Online 中打开

The code is great! thanks. A couple of questions (if you prefer, I can ask them at the page where I downloaded the file):

1- Is there a way to to come up with a good approximate for the threshold value? right now I do it by comparing (with my eyes) the actual image and the binary one! I added a loop in case I know the surface fraction but this might not be the case. here is how I did it:

while abs(1-sum(sum(binaryImage))/1200^2-VF)>0.01
    if 1-sum(sum(binaryImage))/1200^2>VF
        thresholdValue=thresholdValue-1;
        binaryImage = originalImage > thresholdValue;
    else
        thresholdValue=thresholdValue+1;
        binaryImage = originalImage > thresholdValue;
    end
    i=i+1
end

2- Right now, the center of the disks are not saved. In my own code, I used a for loop to save them. I wrote this code for a very simple 3D image wherein every 2D cross section (i.e. Image(:,:,i)) is like coins.png in your code. I aslos assumed that I know the number of the disks. Is there any other method to implement this in your code?

function [Centroid_f] = Centroid_finder(Image,n_of_F)

% the inputs to this function are:

% Image=a 3D binary matrix

% n_of_F= number of the fibers/disks/ cylinders in the matrix

%output is the centroids of the fibers within the matrix

Size3=size(Image);

Size=Size3(3);

Centroid_f=zeros(n_of_F,2,Size);

for k=1:Size

    C=Image(:,:,k);
    cc = bwconncomp(C);
    s = regionprops(cc, 'PixelIdxList', 'Centroid');
%     pause
    for i=1:n_of_F
        Centroid_f(i,:,k)=s(i).Centroid;
    end
end

end

3- How can I change the code so that the input could be a 3D greyscale image? I THINK THIS IS VERY DIFFICULT! I was thinking about choosing n sections of the 3D matrix to construct n 2D images in grey scale. Then, use your code for each section. Even in this case, I might have to run this code for at least 100 times! is it a good idea to put the whole code in a "for" loop (since I will know how many sections/2D images I have) and then run it? i.e. :

for i=1:n

...

Image2D(i)=imread(['section'num2str(i),'.png']);

...

end

4- How can I keep track of the movements of the centers? i.e. let's say I move the disks in one image and create another image. Now, how can I connect the corresponding disks?

regards,

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number of disks in a grey scale Image

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