matlab: texture classification

Question

I have a histology image like this:

binary histology image

From the image, we can observe there are two kinds of different cells.

cell type 1 and cell type 2

Is there any way that I can separate these two types of cells into two groups?

• Cape Code: I would suggest the tag 'image' for this kind of questions.

Answer 1

How about using your raw image and previous code to achieve this?

% % % your old code
I=imread(file);
t1=graythresh(I);
k1=im2bw(I,t1);
k1=~k1;
se = strel('disk',1);
k0=imfill(~k1,'holes'); 
cc = conncomp(k0); 
k0(cc.PixelIdxList{1})=0; 
k1=imfill(k1,'holes');
mask=k0 | k1;
%%%%%%%%%%%%%%%%%%

This will give you:

enter image description here

I=rgb2hsv(I); 
I=double(I);
I1=I(:,:,1); % again, the channel that can maximizing the margin between donut and full circle
Imask=(I1-0.2).*(I1-0.9)<0;
k2=mask-Imask;
k2=bwareaopen(k2,100);

This will give you:

enter image description here

k2=mask-Imask;
I2=zeros(size(I1,1),size(I1,2),3);
I2(:,:,1)=(k2==1)*255;
I2(:,:,3)=((I1-0.2).*(I1-0.9)<0)*255;
imshow(I2)

will finally give you (the two types are stored in two channels in the rgb image):

enter image description here

Answer 2

I would use regionprops

props=regionprops(YourBinaryImage, 'Solidity');

The objects with a high solidity will be the disks, those with a lower solidity will be the circles.

(Edit) More formally:

I=imread('yourimage.jpg');
Bw=~im2bw(I, 0.5);
BWnobord = imclearborder(Bw, 4); % clears the partial objects
Props=regionprops(BWnobord, 'All');
solidity=cell2mat({Props.Solidity});
Images={Props.Image}; 

Access the elements of Images where the value in solidity is higher than 0.9 and you get your disks. The circles are the other ones.

Hope it helps