How do I extract size (in terms of pixels) from an image?

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Andrea Labudzki 2021-11-22

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https://ww2.mathworks.cn/matlabcentral/answers/1593094-how-do-i-extract-size-in-terms-of-pixels-from-an-image

评论： Andrea Labudzki 2021-12-1

Hello everyone. I have an image like the following:

It is converted to grayscale and binarized. I would like to extract information about the size of the white "holes" and the black "lines." I know that the image consists of a matrix with the 0 and 1 values, but how can I extract this information to figure out the size of each individual hole and line? (I've been staring at this problem for like a week and my brain is frozen...pls help).

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DGM 2021-11-22

Do you need the size of every individual hole and wire, or just some typical (e.g. mean) size? Do you need this to be automated for many images, or just this one?

You may run into problems making a robust automated solution for the "every hole" case unless you can come up with a good way to identify the debris.

Andrea Labudzki 2021-11-22

I need it for every hole and wire, though I am able to omit certain parts of the image if they are problematic. I need it to work for various images. The user should be able to input their image and I want to eventually be able to provide analysis for whether the hole and wire sizes fulfill certain certification standards.

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Answer 1

Image Analyst 2021-11-22

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https://ww2.mathworks.cn/matlabcentral/answers/1593094-how-do-i-extract-size-in-terms-of-pixels-from-an-image#answer_837804

在 MATLAB Online 中打开

Try this:

% Demo by Image Analyst
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 = 20;
markerSize = 40;
%--------------------------------------------------------------------------------------------------------
%    READ IN IMAGE
fileName = 'grid.PNG';
grayImage = imread(fileName);
% 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.
    % Extract the blue channel (so the magenta lines will be white).
    grayImage = grayImage(:, :, 3);
end
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
axis('on', 'image');
title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
hold on
drawnow;
% Maximize window.
g = gcf;
g.WindowState = 'maximized'
drawnow;
subplot(2, 2, 2);
imhist(grayImage);
grid on;
low = 133;
high = 255;
% Interactively/visually select the threshold
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle
% [low, high] = threshold(low, high, grayImage)
mask = grayImage > low;
% Fill holes.
mask = imfill(mask, 'holes');
% Display the image.
subplot(2, 2, 3);
imshow(mask, []);
impixelinfo;
axis('on', 'image');
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
hold on
drawnow;
% Label each blob with 8-connectivity, so we can make measurements of it
[labeledImage, numberOfBlobs] = bwlabel(mask, 8);
% Apply a variety of pseudo-colors to the regions.
coloredLabelsImage = label2rgb (labeledImage, 'hsv', 'k', 'shuffle');
% Display the pseudo-colored image.
% Display the image.
subplot(2, 2, 4);
imshow(coloredLabelsImage);
impixelinfo;
axis('on', 'image');
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
hold on
drawnow;
% Get all the blob properties.  Can only pass in originalImage in version R2008a and later.
props = regionprops(labeledImage, grayImage, 'Area');
numberOfBlobs = size(props, 1);
% Get a list of all the areas
allAreas = [props.Area];
% Compute the mean area.
meanArea = mean(allAreas)
% Show the histogram.
figure
histogram(allAreas);
grid on;
xline(meanArea, 'Color', 'r', 'LineWidth', 3)
caption = sprintf('Distribution of %d Areas.  Mean Area = %.2f pixels.', numberOfBlobs, meanArea)
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Area', 'FontSize', fontSize, 'Interpreter', 'None');
ylabel('Count', 'FontSize', fontSize, 'Interpreter', 'None');

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Image Analyst 2021-12-1

在 MATLAB Online 中打开

Yes. If you have the stats toolbox, simply call pdist2() to get the distance between centroids

props = regionprops(labeledImage, grayImage, 'Area', 'BoundingBox', 'Centroid');
% Get bounding boxes.
bb = vertcat(props.BoundingBox);
widths = bb(:, 3);
heights = bb(:, 4);
centroids = vertcat(props.Centroid);
distancesMatrix = pdist2(centroids, centroids);
histogram(distancesMatrix);

There should be peaks in the distribution around the spacing (for neighbors up, down, left, right) and sqrt(2) times the spacing (for diagonal neighbors).

Andrea Labudzki 2021-12-1