how do I draw discriminatory lines in an image to calculate the area in each of those regions?

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Neo 2023-1-9

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评论： Image Analyst 2023-1-15

Hello, I am exploring matlab and I was wondering how do i draw circular lines that classify particular regions of that image? So that later on I can calculate the area of that region seperatley than the other regions?

I have several images and I am wondering which methods I can use to segment regions within that image from other regions in that same image.

Thank you

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Neo 2023-1-9

Or a method to calculate the area of a region within an image.

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Image Analyst 2023-1-10

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See the FAQ:

https://matlab.fandom.com/wiki/FAQ#How_do_I_create_a_circle?

See my Image Processing Tutorial in my File Exchange:

Image Analyst's File Exchange

See attached drawing demos.

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Image Analyst 2023-1-10

在 MATLAB Online 中打开

If you just want the mean gray level in 12 strips going across the image, try this:

% Demo by Image Analyst

% Find the mean gray level in 12 strips going across the image.

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;

markerSize = 40;

%--------------------------------------------------------------------------------------------------------

% READ IN IMAGE

folder = [];

baseFileName = 'cameraman.tif';

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

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)

rows = 256

columns = 256

numberOfColorChannels = 1

if numberOfColorChannels > 1

% It's not really gray scale like we expected - it's color.

fprintf('It is not really gray scale like we expected - it is color\n');

% Extract the blue channel.

grayImage = rgb2gray(grayImage);

end

%--------------------------------------------------------------------------------------------------------

% Display the image.

subplot(1, 3, 1);

imshow(grayImage);

impixelinfo;

axis('on', 'image');

title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');

% Update 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)

rows = 256

columns = 256

numberOfColorChannels = 1

% Maximize window.

g = gcf;

g.WindowState = 'maximized';

drawnow;

%--------------------------------------------------------------------------------------------------------

% Get mean across 12 vertical bands of the image

startingColumns = round(linspace(1, columns+1, 13))

startingColumns = 1×13

1 22 44 65 86 108 129 150 172 193 214 236 257

endingColumns = startingColumns(2:end) - 1

endingColumns = 1×12

21 43 64 85 107 128 149 171 192 213 235 256

for k = 1 : length(endingColumns)

col1 = startingColumns(k);

col2 = endingColumns(k);

% Make a strip

mask = false(size(grayImage));

mask(:, col1:col2) = true;

subplot(1, 3, 2);

imshow(mask);

impixelinfo;

axis('on', 'image');

caption = sprintf('Mask #%d', k);

title(caption, 'FontSize', fontSize, 'Interpreter', 'None');

% Crop the image so we get the image in the mask

subImage = grayImage(:, col1 : col2);

subplot(1, 3, 3);

imshow(subImage);

impixelinfo;

axis('on', 'image');

caption = sprintf('Subimage #%d', k);

title(caption, 'FontSize', fontSize, 'Interpreter', 'None');

drawnow;

% Make measurements of mean graylevel.

meanGL(k) = mean(grayImage(mask));

end

meanGL

meanGL = 1×12

146.379836309524 124.317294034091 73.9890252976191 60.8411458333333 85.0129616477273 95.8610491071429 126.819754464286 140.714133522727 144.698474702381 147.955357142857 143.329190340909 133.895833333333

Image Analyst 2023-1-13

在 MATLAB Online 中打开

That's not an RGB image so all that stuff about RGB images does not apply. It's just a gray scale image so my original code should work:

% Demo by Image Analyst
% Find the mean gray level in 12 strips going across the image.
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;
markerSize = 40;
%--------------------------------------------------------------------------------------------------------
%    READ IN IMAGE
folder = [];
baseFileName = 'testrgbimage.tif';
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.
    fprintf('It is not really gray scale like we expected - it is color\n');
    % Extract the blue channel.
    grayImage = rgb2gray(grayImage);
end
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(1, 3, 1);
imshow(grayImage, []);
impixelinfo;
axis('on', 'image');
title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Update 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)
% Maximize window.
g = gcf;
g.WindowState = 'maximized';
drawnow;
%--------------------------------------------------------------------------------------------------------
% Get mean across 12 vertical bands of the image
startingColumns = round(linspace(1, columns+1, 13))
endingColumns = startingColumns(2:end) - 1
for k = 1 : length(endingColumns)
    col1 = startingColumns(k);
    col2 = endingColumns(k);
    % Make a strip
    mask = false(size(grayImage));
    mask(:, col1:col2) = true;
    subplot(1, 3, 2);
    imshow(mask);
    impixelinfo;
    axis('on', 'image');
    caption = sprintf('Mask #%d', k);
    title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
    % Crop the image so we get the image in the mask
    subImage = grayImage(:, col1 : col2);
    subplot(1, 3, 3);
    imshow(subImage);
    impixelinfo;
    axis('on', 'image');
    caption = sprintf('Subimage #%d', k);
    title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
    drawnow;
    % Make measurements of mean graylevel.
    meanGL(k) = mean(grayImage(mask));
end
meanGL

Neo 2023-1-13

If you just want the mean gray level in 12 strips going across the image:

@Image Analyst

What does it mean to have the measure the gray level? Also how to read the output ?

startingColumns =

1 44 86 129 172 214 257 300 342 385 428 470 513

endingColumns =

43 85 128 171 213 256 299 341 384 427 469 512

Image Analyst 2023-1-13

The gray level is the brightness of the image pixels.

Those values are the starting and stopping columns of the vertical strip where we are going to get the mean intensity in.

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Matt J 2023-1-9

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1890817-how-do-i-draw-discriminatory-lines-in-an-image-to-calculate-the-area-in-each-of-those-regions#answer_1144817

编辑：Matt J 2023-1-9

I was wondering how do i draw circular lines

You can use drawcircle.

More generally, you can segment interactively with the Segmenter App

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Neo 2023-1-14

@Image Analyst

i am not sure if this should be a seperate question but before I take the mean gray level in the strips, I would like to substract the background, correct for contrast, implement gaussian filtering and thresholding/binarization so i have added this code that i found from other matlab answers:

% Binarize the image.

mask = grayImage > lowThreshold & grayImage < highThreshold;

mask = imfill(mask, 'holes');

% Find out the areas

props = regionprops(mask, 'Area');

allAreas = sort([props.Area], 'descend')

% Take only blobs 20 pixels or larger

mask = bwareaopen(mask, 20);

% Update measurements.

props = regionprops('table', mask, grayImage, 'Area', 'MeanIntensity', 'MaxIntensity', 'MinIntensity');

allAreas = [props.Area]

meanIntensities = [props.MeanIntensity]

maxIntensities = [props.MaxIntensity]

minIntensities = [props.MinIntensity]

% Display the mask.

subplot(2, 2, 3);

imshow(mask, []);

title('Mask', 'FontSize', fontSize, 'Interpreter', 'None');

axis('on', 'image');

maskedImage = grayImage; % Initialize.

maskedImage(~mask) = 0; % Or whatever gray level you want, such as mean(grayImage(~mask));

% Display the image.

subplot(2, 2, 4);

imshow(maskedImage, []);

title('Masked Image', 'FontSize', fontSize, 'Interpreter', 'None');

axis('on', 'image');

what do you think?

Neo 2023-1-15

I have asked it in another question but I cant tell that it has been performed background substraction, gaussian and contrast correction before mean grey level analysis. How can you?

Image Analyst 2023-1-15

I don't see anything being subtracted from the gray scale image in the code above. You need to read in a background image and then subtract it. Decide where you want to discuss this. I suggest your new thread just about background subtraction. (Note spelling of subtraction -- there are not two s's).

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