RGB colored image segmentation

Hi all,

I have an RGB colored histology slide. I am getting blue and green components in this image by,

imgG=IMG(:,:,2); imgB=IMG(:,:,3);

However, l don't want to see these imgG and imgB images as grayscale. I want to see these parts with their original color and texture that are in the IMG. How to do this?

My second question is: l want to have information about vector flow of the segmented parts to see directions. Could you please help me how to do this? Thanks

Answer 1

[Walter Roberson]

imgG = IMG; imgG(:,:,[1 3]) = 0;
imgB = IMG; imgB(:,:,[1 2]) = 0;
imgR = IMG; imgR(:,:,[2 3]) = 0;

Second question

You can calculate gradient information. Once you have it, you can quiver() to display it.

Answer 2

[Image Analyst]

You need to make up color maps, such as

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 long g;
format compact;
fontSize = 20;

%===============================================================================
% Read in a demo image.
folder = fileparts(which('peppers.png')); % Determine where demo folder is (works with all versions).
baseFileName = 'peppers.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileNameOnSearchPath = baseFileName; % No path this time.
  if ~exist(fullFileNameOnSearchPath, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Display the image.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis on;
title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorChannels] = size(rgbImage);

% 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') 

% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);

% Display the image.
hImage = subplot(2, 2, 2);
imshow(redChannel, []);
axis on;
title('Red Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Create a colormap for red.
axes(hImage);
z = zeros(256,1);
ramp = linspace(0, 1, 256)';
cmap = [ramp, z, z];
colormap(hImage, cmap);
colorbar;

% Display the image.
hImage = subplot(2, 2, 3);
imshow(greenChannel, []);
axis on;
title('Green Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Create a colormap for red.
z = zeros(256,1);
ramp = linspace(0, 1, 256)';
cmap = [z, ramp, z];
colormap(hImage, cmap);
colorbar;

% Display the image.
hImage = subplot(2, 2, 4);
imshow(blueChannel, []);
axis on;
title('Blue Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Create a colormap for red.
z = zeros(256,1);
ramp = linspace(0, 1, 256)';
cmap = [z, z, ramp];
colormap(hImage, cmap);
colorbar;

[Image Analyst]

For the second question about optical flow, you'll have to use the optical flow capability in the Computer Vision System Toolbox.