Create new binary image from pixel values of another image

I have a grayscale uint8 image, and I want to create a second image that is mostly zeros, but has a 1 wherever the pixel value in the first image is equal to a specific value. So, if my image was a 5x5 image such as:

    17    24     1     8    15
    23     5     7    14    16
     4     6    13    20    22
    10    12    19    21     3
    11    18    25     2     9

and I want to 'get' all values equal to 13, the result would be:

     0     0     0     0     0
     0     0     0     0     0
     0     0     1     0     0
     0     0     0     0     0
     0     0     0     0     0

I'm sure this task is really simple, but I'm having problems working out how to do it - I would appreciate anyone's help.

Answer 1

[Image Analyst]

Yes it is very simple - just one single line. Simply say:

M_matched = M == matchValue;

Where M is your input matrix, matchValue is the value you want to find (e.g. 13), and M_matched is the output matrix. M_Matched is a logical matrix (which is the data type of "binary" images). A logical (binary) matrix is convenient because you can then use it for logical indexing to extract certain values from a matrix. For example you can say

M_extracted = M(M2);

M_extracted will be 13 in your example but it could be several 13's if you have more than one 13 or other values if you use ">=" instead of "==" in my first line of code.

But you can also cast M_matched to int32 or double or whatever you want, if you need to do that.

[Philip]

Thanks - I knew it would be easy!

Just to add a complication, what could I do if I wanted to use M_matched as a mask to another image, where the 1s represent the locations for extracting pixels in a third image?

[Image Analyst]

See formatted code below in another Answer. If you consider it solved, mark it as "answered"

[Rizwan Chughtai]

if i have 2 matrices:

A=

    17    24     1     8    15     
    23     5     7    14    16
     4     6    13    20    22
    10    12    19    21     3
    11    18    25     2     9

B=

    0     0     1    1    0     
    0     1     1    0    0
    1     1     1    0    0
    1     1     0    0    1
    1     0     0    1    1

How do we know that the threshold is 13.

i mean, what fuction should i apply on these two matrices (A and B), so the we automatically get the answer that threshold is 13 (above 13 is '0' and below 13 is '1')?

kindly tell me the function OR something @image anylst

[Image Analyst]

That's a new B, not one just listing pixels that are 13 like your first example. This B seems to be

B = A <= 13;

If you don't know or have the 13 yet, but DO have the B array, you can do

threshold = max(A(B));

Then you'd get B again by doing

B = A <= threshold;

[Rizwan Chughtai]

Thank you @image anaylst

Answer 2

[Andrei Caragea]

Try this. Let A be the initial matrix, like the one in the example. Do A=A-13; B=ones(size(A)); B(find(A))=0. B will be a matrix like you want.

Answer 3

[Image Analyst]

Response to your comment/question about masking:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
fontSize = 20;

% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'cameraman.tif';
fullFileName = fullfile(folder, baseFileName);
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);
% Display the original gray scale image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') 

% Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(grayImage);
subplot(2, 2, 2); 
bar(pixelCount);
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.

maskImage = grayImage > 80;
% Display the mask image.
subplot(2, 2, 3);
imshow(maskImage, []);
title('Mask Image', 'FontSize', fontSize);

% Mask the image.
% Alternate way:
% maskedImage = bsxfun(@times, grayImage, cast(maskImage,class(grayImage)));
% Mask image must be converted to the same integer type
% as the integer image we want to mask.
% maskImage = cast(maskImage, class(grayImage));
maskedImage = grayImage; % Initialize
maskedImage(maskImage) = 0; % Do the actual masking.
% Display the masked image.
subplot(2, 2, 4);
imshow(maskedImage, []);
title('Masked Image', 'FontSize', fontSize);

[Philip]

Wow, thanks for all your effort with that - it's pretty perfect!