good day all.. i have an image with many unconnected vessels..of pixels i want to remove those pixels how an i do it?
MATLAB: How to remove unconnected pixels or objects from an image
enhancementeyefundusnoiseophthalmologyretinaunconnected pixels
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Please define "isolate".
Vishakha:
You might have to take just one color channel, then get rid of the local intensity variations with a bottom hat filter. Then threshold and call bwareafilt() to get rid of blobs bigger or smaller than the known size of the fibers. Then call bwlabel() to count the number of fibers.
Try this for a start - adapt as needed:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format short g;format compact;fontSize = 25;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'netmuscle.jpg';% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);%===============================================================================% Read in a demo image.
grayImage = imread(fullFileName);% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
% grayImage = rgb2gray(grayImage);
% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
grayImage = grayImage(:, :, 3); % Take blue channel.
end% Display the image.
subplot(1, 2, 1);imshow(grayImage, []);axis on;axis image;caption = sprintf('Original Gray Scale Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;% Do a bottom hat filter to find the small dark spots.
subplot(1, 2, 2);histogram(grayImage);grid on;se = strel('disk', 15);filteredImage = imbothat(grayImage, se);% Display the image.imshow(filteredImage, []);histogram(filteredImage);grid on;% Binarize the image.
% binaryImage = imbinarize(grayImage);
binaryImage = filteredImage >35; % Dtermine number from histogram.
% Make sure there are blobs only between 100 and 800 pixels.
binaryImage = bwareafilt(binaryImage, [100, 800]);% Display the image.subplot(1, 2, 2);imshow(binaryImage, []);axis on;axis image;caption = sprintf('Binary Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Label the image
[labeledImage, numBlobs] = bwlabel(binaryImage);% Make measurements of bounding box
props = regionprops(labeledImage, 'Area');allAreas = [props.Area]sortedAread = sort(allAreas)caption = sprintf('Binary Image with %d Muscle Fibers', numBlobs);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
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