convert white color in image to red color
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Could you please support me by Matlab code to convert white color in any image to red color ?
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Image Analyst
2020년 11월 22일
편집: Image Analyst
2020년 11월 22일
Since you didn't say what "red" means to you, I've done it three different ways:
% Demo to turn white petals of a daisy red. By Image Analyst, Nov. 22, 2020.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clearvars;
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
fprintf('Beginning to run %s.m ...\n', mfilename);
%-----------------------------------------------------------------------------------------------------------------------------------
% Read in image.
folder = [];
baseFileName = 'white-flower.png';
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
% It's not an RGB image! It's an indexed image, so read in the indexed image...
rgbImage = imread(fullFileName);
[rows, columns, numberOfColorChannels] = size(rgbImage)
% Display the test image.
subplot(3, 2, 1);
imshow(rgbImage, []);
axis('on', 'image');
caption = sprintf('Image : "%s"', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
hFig1 = gcf;
hFig1.Units = 'Normalized';
hFig1.WindowState = 'maximized';
% 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.
hFig1.Name = 'Demo by Image Analyst';
% Find a mask of just the white pixels.
[mask, maskedRGBImage] = createMask(rgbImage);
% Display the mask image.
subplot(3, 2, 2);
imshow(mask, []);
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
axis('on', 'image');
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the initial mask image.
subplot(3, 2, 3);
imshow(maskedRGBImage, []);
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
axis('on', 'image');
title('Masked RGB Image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
%-----------------------------------------------------------------------------------
% Option 1 : make the white pure red or (255, 0, 0)
% Get the individual RGB channels
[redChannel, greenChannel, blueChannel] = imsplit(rgbImage);
% Make the image pure red in the mask regions
redChannel(mask) = 255;
greenChannel(mask) = 0;
blueChannel(mask) = 0;
% Recombine separate color channels into a single, true color RGB image.
tintedRgbImage = cat(3, redChannel, greenChannel, blueChannel);
% Display the initial mask image.
subplot(3, 2, 4);
imshow(tintedRgbImage, []);
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
axis('on', 'image');
title('Tinted RGB Image via Setting to a Constant', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
%-----------------------------------------------------------------------------------
% Option 2 : make the white redder than it is by multiplying it by some brightness reduction factor.
% Get the individual RGB channels
[redChannel, greenChannel, blueChannel] = imsplit(rgbImage);
% Make the image redder in the mask regions by lowering the green and blue channels.
brightnessReductionFactor = 0.35;
greenChannel(mask) = uint8(brightnessReductionFactor * double(greenChannel(mask)));
blueChannel(mask) = uint8(brightnessReductionFactor * double(blueChannel(mask)));
% Recombine separate color channels into a single, true color RGB image.
tintedRgbImage = cat(3, redChannel, greenChannel, blueChannel);
% Display the initial mask image.
subplot(3, 2, 5);
imshow(tintedRgbImage, []);
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
axis('on', 'image');
title('Tinted RGB Image via Multiplication', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
%-----------------------------------------------------------------------------------
% Option 3 : make the white redder than it is by subtracting some brightness factor.
% Get the individual RGB channels
[redChannel, greenChannel, blueChannel] = imsplit(rgbImage);
% Make the image redder in the mask regions by lowering the green and blue channels.
subtractionAmount = uint8(150);
greenChannel(mask) = greenChannel(mask) - subtractionAmount;
blueChannel(mask) = blueChannel(mask) - subtractionAmount;
% Recombine separate color channels into a single, true color RGB image.
tintedRgbImage = cat(3, redChannel, greenChannel, blueChannel);
% Display the initial mask image.
subplot(3, 2, 6);
imshow(tintedRgbImage, []);
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
axis('on', 'image');
title('Tinted RGB Image via Subtraction', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
fprintf('Done running %s.m ...\n', mfilename);
msgbox('Done!');
function [BW,maskedRGBImage] = createMask(RGB)
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 22-Nov-2020
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.000;
channel1Max = 1.000;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;
channel2Max = 0.374;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.467;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
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