How to detect white regions in image
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I have a code below to detect exudates from retina Images
clc;
close all;
clear all;
workspace; % Display workspace panel.
% filename = 'C:\Documents and Settings\tk2013\My Documents\Temporary
% stuff\fundus.jpg';
rgbImage = imread('2.jpg');
[rows columns numberOfColorPlanes] = size(rgbImage);
subplot(3, 3, 1);
imshow(rgbImage, []);
title('Original color Image');
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
tic;
redPlane = rgbImage(:, :, 1);
greenPlane = rgbImage(:, :, 2);
figure,imshow(redPlane)
K = imadjust(redPlane);
figure
imshow(K)
SE = strel('rectangle',[7 5]);
BW3 = imdilate(K,SE);
figure,imshow(BW3)
s=strel('square',12);
h=(imclose(BW3,s));
figure,imshow(h)
greenPlane=h;
[pixelCountsG GLs] = imhist(greenPlane);
% Ignore 0
pixelCountsG(1) = 0;
% Find where histogram falls to 10% of the peak, on the bright side.
tIndex = find(pixelCountsG >= .1*max(pixelCountsG), 1, 'last');
thresholdValue = GLs(tIndex)
binaryGreen = greenPlane>thresholdValue;
binaryImage = imfill(binaryGreen, 'holes');
% Get rid of blobs less than 5000 pixels.
binaryImage = bwareaopen(binaryImage, 5000);
figure,imshow(binaryGreen)
but the final output is only black,kindly help to extract the exudates from the above code,I have attached the images,I tried with different thresholds but could not get answer
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Respuestas (2)
Image Analyst
el 11 de Nov. de 2014
So much wrong but I don't have time to fix it all. For starters, comment out the bwareaopen() function. And plot the histogram so you can see its shape.
2 comentarios
Image Analyst
el 12 de Nov. de 2014
The red plane will have the least contrast. The blue or green channel will have more. That's why in my code I chose the green channel. But then you inserted code to adjust and do morphology on the red channel and then stick that modified red channel image into a variable deceptively named greenChannel.
I'm not going to have time to look at this for several days, if at all, so I ask you to look at algorithms published here http://www.visionbib.com/bibliography/contentsmedical.html#Medical%20Applications,%20CAT,%20MRI,%20Ultrasound,%20Heart%20Models,%20Brain%20Models in Section 20.5, where people show how they've successfully done it. There is no need to invent your own algorithm when people have been working for months or years on algorithms and have published them for you to simply implement.
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