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how to change the color of pixels in a binary image?

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bamini thavarajah 2017-12-1

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/370483-how-to-change-the-color-of-pixels-in-a-binary-image

评论： bamini thavarajah 2017-12-5

采纳的回答： Image Analyst

I want to generating random pixels on edge boundary and give red color to that pixels. Thanks in advance.

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Rik 2017-12-1

A binary image has only 2 colors. Depending on what method you choose to display it, you can choose the two colors yourself.

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采纳的回答

Image Analyst 2017-12-2

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https://ww2.mathworks.cn/matlabcentral/answers/370483-how-to-change-the-color-of-pixels-in-a-binary-image#answer_294293

testGrayImage.m

See attached m-file.

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Image Analyst 2017-12-3

在 MATLAB Online 中打开

What about this:

% Initialization / clean-up code.
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 = 25;
%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'apple-1.gif';
% 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.
binaryImage = 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(binaryImage)
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.
  binaryImage = rgb2gray(binaryImage);
  % 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, 3, 1);
imshow(binaryImage, []);
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;
% Get the edges.
binaryImage = edge(binaryImage,'Sobel');
% Display the image.
subplot(2, 3, 2);
imshow(binaryImage, []);
axis on;
axis image;
caption = sprintf('Edge Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Let's find the location of all the white pixels:
[rows, columns] = find(binaryImage)
% Get 30 random locations
randomIndexes = randperm(length(rows), 30);
% Get a new binary image
redDots = false(size(binaryImage));
for k = 1 : length(randomIndexes)
  redDots(rows(randomIndexes(k)), columns(randomIndexes(k))) = true;
end
% Display the image.
subplot(2, 3, 3);
imshow(redDots, []);
% Dilate the red channel
redChannel = binaryImage | imdilate(redDots, true(5,6));
% Display the image.
subplot(2, 3, 4);
imshow(redChannel, []);
% Wherever red channel is set, make blue and green channels black there.
greenChannel = binaryImage; % Initialize
blueChannel = binaryImage; % Initialize
greenChannel(~redChannel) = 0;
blueChannel(~redChannel) = 0;
% Create an RGB image so we can have red pixels.
redChannel = 255 * uint8(redChannel);
greenChannel = 255 * uint8(greenChannel);
blueChannel = 255 * uint8(blueChannel);
rgbImage = cat(3, redChannel, greenChannel, blueChannel);
% Display the image.
subplot(2, 3, 5);
imshow(rgbImage, []);
axis on;
axis image;
caption = sprintf('Modified Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
redPixels = rgbImage(:,:,1)==255 & rgbImage(:,:,2)==0 & rgbImage(:,:,3)==0;
numRedPixels = sum(redPixels(:))

Image Analyst 2017-12-5

The image will be red anywhere the red value is non-zero and the green and blue values are both 0. If that describes the whole image, then it's the whole image. If that describes only some pixels in the image, then only those pixels will be red.

bamini thavarajah 2017-12-5

thanks a lot sir for spent your time for me. I understood & I got the answer.

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