CODEWITHSUNDEEP
matlabimage-processing
ANUSHA DEVI
ANUSHA DEVI

Reputation: 225

Conversion to binary : Matlab

I am trying to extract veins using thinning algorithm. So far i did this much of code for image enhancement and its pretty much working. But when i computed binary thresholding i am not able to identify the veins from the back ground.Due to a vague output i am not able to do further processing for thinning. Can any one tell me whats wrong in this code? or is it because the threshold has to be done in some other way.

a=imread('vein.jpg');
cform = makecform('srgb2lab');
for ii = 1:3
  a(:,:,ii) = medfilt2(a(:,:,ii),[5 5]);
end
lab = applycform(a,cform); 
b=lab(:,:,1);
c=im2bw(b,0.2);
neg=1-c;
color=a;
r=color(:,:,1);
r(~c)= 0;
g = color(:,:,2);
g(~c)= 0;
b = color(:,:,3);
b(~c)= 0;
color = cat(3,r,g,b);
gray=rgb2gray(color);
i1=imresize(gray,[256 256],'bilinear');
i2=histeq(i1,256);
e=medfilt2(i2,[5 5]);
figure(1),imshow(e);
f=medfilt2(e,[5 5]);
figure(2),imshow(f);
thresh_level = graythresh(g); 
BW = im2bw(g, thresh_level);          
figure(10),imshow(BW);

original image enhanced image BINARIZED

Upvotes: 1

Views: 92

Answers (1)

xenoclast
xenoclast

Reputation: 1635

greythresh uses Otsu's method, which is a good general method that works on the distribution of intensities. However it's not ideal for every situation, particularly if you've applied lots of nonlinear processing to the image first (e.g. clipping the channels).

You could try to generate your own threshold - look at the intensity distribution or, since you have them, the distribution in the colour channels and see if there's a plausible place to separate them. You could try to model it as a mixture of Gaussians (2 seems like a good number to start with, look up gmdistribution.fit) or do some other type of clustering. Is there any information in the colour channels that you could use?

If you end up the other way - with veins that are much darker but are continuous - then you could use morphological operators on the binarised image to get it back to the expected range. Perhaps this is what the thinning algorithm does.

Upvotes: 0

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