MATLAB: How to filter an RGB image and transform into an BW one.

imageimage analysisimage processingImage Processing ToolboxMATLAB

I have been trying to do that:

http://prntscr.com/umv66 -> http://goo.gl/Bgmv2 (You can ignore the red lines, I just added them to illustrate the final objective)

So, what I've done in the first case was: I transformed rgb -> hsv and picked up the s channel (a.k.a saturation). Then I used Otsu (called graythresh in matlab) to binarize and transform into a black and white picture. Everything worked perfectly.

Now, in the second case this doesn't work so well:

Base img( http://goo.gl/OtK4G) -> S Channel( http://goo.gl/oo8h6>) ->Otsu( http://goo.gl/cnfxU)

As you can see, the Otsu filter becomes useless in this case. Is there any workaround or other way I should be taking? Thanks in advance!

Best Answer

I think you need to try some noise removal first. You can try a median filter first because it's easy. If that doesn't work, try a bilateral filter or a mean shift filter. After that you should be able to threshold it reasonably well in the Saturation channel. If you look at the image's 3D color gamut you'll see that it is like a slab but it's not radial along a constant hue - it's tilted in the Hue-Saturation plane, so to do the best job of segmentation you'll need to do principal components analysis and find the axis and then threshold in the PC2 or PC3 component. You could do the PCA in either RGB color space or HSV colorspace. However, if you look at it in LAB color space, it's pretty much has a constant "b" value with varying "a" value. So use makecform to convert to lab colorspace and threshold the "a" channel, after noise reduction of course. That would be my recommendation after inspecting the gamut with this.

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MATLAB: Obtain average image threshold without the background

Try this:

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 = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'image.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	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
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(:, :, 2); % Take green channel.
end
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image of just the blob and not including the black background or the white surround.
mask = grayImage > 0 & grayImage < 255;  %imbinarize(grayImage);
subplot(2, 2, 2);
imshow(mask, []);
impixelinfo;
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Display histogram of image but only the image within the mask
subplot(2, 3, 4);
histogram(grayImage(mask), 0:255);
grid on;
title('Histogram of gray image', 'FontSize', fontSize);
% Now get the threshold
thresh = 255 * graythresh(grayImage(mask))
% Put a red line there at the threshold
xline(thresh, 'Color', 'r', 'LineWidth', 2);
% Get a binary image of the bright stuff
brightStuff = grayImage >= thresh & mask;
subplot(2, 3, 5);
imshow(brightStuff, []);
impixelinfo;
title('Bright Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
subplot(2, 3, 6);
darkStuff = ~brightStuff & mask;
imshow(darkStuff, []);
impixelinfo;
title('Dark Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;

MATLAB: How to correction hue values of image

You need to snap an image of a color standard with known color values. The usual standard is the x-rite Color Checker Chart. Then you have known XYZ values. You can use least squares to derive a transform to convert your RGB values, of the color chips on a picture of that chart that you have taken, into XYZ values. Then you can use analytical formulas to convert XYZ into LAB or other calibrated color spaces.

Best Answer

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MATLAB: Obtain average image threshold without the background

MATLAB: How to correction hue values of image

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