![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/346617/image.png)
How to find pixel in one square block?
9 views (last 30 days)
Show older comments
Hello,
I have an Image called checkerboard, now i know the size of one square block is 34 x 34 mm. how can i find that in that one square block 34mm has how many pixel?
is there any formula to find or function?
Thank you in advance.
0 Comments
Accepted Answer
Image Analyst
on 16 Aug 2020
Try this. You'll find meanArea = 102.3 pixels.
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 = 'checkerboard.jpg';
% 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;
% Display histogram
subplot(2, 2, 2);
imhist(grayImage);
grid on;
title('Histogram of original gray image', 'FontSize', fontSize);
%--------------------------------------------------------------------------------------------------------
% SEGMENTATION OF IMAGE
binaryImage = grayImage < 40;
% Display the image.
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Measure areas
labeledImage = bwlabel(binaryImage, 4);
props = regionprops(labeledImage, 'Area', 'BoundingBox');
allAreas = [props.Area]
bb = vertcat(props.BoundingBox);
widths = bb(:, 3);
heights = bb(:, 4);
aspectRatios = widths ./ heights
keepers = find(allAreas' > 80 & aspectRatios > 0.8 & aspectRatios < 1.3);
% Get new image with just the squares.
binaryImage = ismember(labeledImage, keepers);
% Display the image.
subplot(2, 2, 4);
imshow(binaryImage, []);
title('New Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Measure areas of only hte "good" blobs.
labeledImage = bwlabel(binaryImage, 4);
props = regionprops(labeledImage, 'Area', 'BoundingBox');
allAreas = [props.Area]
meanArea = mean(allAreas)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/346617/image.png)
13 Comments
Image Analyst
on 19 Aug 2020
Just invert it and multiply by 34, but it really shouldn't even be necessary since we're not ever going to use that information, remember?
% Pixels = mm * pixels/mm
mmPerPixel = sqrt(areaInMm / areaInPixels);
pixelsPerMm = 1 / mmPerPixel; % or sqrt(areaInPixels / areaInMm)
pixelDistance34 = 34 * pixelsPerMm % Number of pixels across a 34 mm span.
More Answers (1)
Walter Roberson
on 16 Aug 2020
Use bwconncomp with connection 4. Pass the result to regionprops asking for BoundingBox . You will get a struct array returned. You can put them together into one array using vertcat(). Now you can use median() on the 3rd and 4th columns to find out what the median box size is in pixels. Then knowing that represents 34 mm of physical space, you can calculate the image resolution.
2 Comments
See Also
Categories
Find more on Image Processing Toolbox in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!