How to use "regionprops" function on true color image?!
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Hey Everybody, hope you are all doing well;
i am trying to get the Max and mean intensity through regionprops function using the following command:
CC = bwconncomp(Img.jpg);
Label2=labelmatrix (CC);
rgb_labeled=label2rgb(Label2);
imshow(rgb_labeled);
but receive the following Error message:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
??? Error using ==> iptcheckinput
Function LABEL2RGB expected its first input, L, to be two-dimensional.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Regarding that when i entered the image as and RGB or intensity (gray) image as an input for regionprops function, the following error displayed..
Error message:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
??? Error using ==> regionprops>getPropsFromInput at 1172
REGIONPROPS needs I as an input to calculate 'MaxIntensity'.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Waiting your help, thanks A lot...
4 Kommentare
Walter Roberson
am 22 Jun. 2013
Oh, I'm not a doctor, but if you have some spare honorary degrees you might be able to persuade me to change that.
Antworten (2)
Image Analyst
am 14 Jun. 2013
You need to extract the color channels:
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
and then do regionprops on each color channel one at a time.
12 Kommentare
Image Analyst
am 25 Jun. 2013
Bearbeitet: Image Analyst
am 25 Jun. 2013
Miriam, again, you need to run regionprops() with a binary image. And if you want intensity info, you'll have to pass in the gray scale image also. Here, run this code and study what it does:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures if you have the Image Processing Toolbox.
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;
% Read in a standard MATLAB color demo image.
folder = 'D:\Temporary stuff';
baseFileName = 'es8u.jpg';
% 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
rgbImage = imread(fullFileName);
% Get the dimensions of the image. numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 3, 1);
imshow(rgbImage);
title('Original Color Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Display the color channels
subplot(2, 3, 4);
imshow(redChannel);
title('Red Channel Image', 'FontSize', fontSize);subplot(2, 3, 2);
subplot(2, 3, 5);
imshow(greenChannel);
title('Green Channel Image', 'FontSize', fontSize);subplot(2, 3, 2);
subplot(2, 3, 6);
imshow(blueChannel);
title('Blue Channel Image', 'FontSize', fontSize);
% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(greenChannel);
% Suppress pure black so we can see the histogram.
pixelCount(1) = 0;
subplot(2, 3, 2);
bar(pixelCount);
grid on;
title('Histogram of Green Channel', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Create a binary image
binaryImage = greenChannel > 13;
% Fill holes
binaryImage = imfill(binaryImage, 'holes');
% Get rid of small specks.
binaryImage = bwareaopen(binaryImage, 10000);
subplot(2, 3, 3);
imshow(binaryImage);
title('Binary Image', 'FontSize', fontSize);
% Get the mean of the red and blue channel
% within the white pixels of the binary image using one method.
redMean = mean(redChannel(binaryImage))
blueMean = mean(blueChannel(binaryImage))
% Get the mean of the green channel
% within the white pixels of the binary image using one method.
measurements = regionprops(binaryImage, greenChannel, 'MeanIntensity');
greenMean = measurements.MeanIntensity
message = sprintf('The mean red intensity = %.2f.\nThe green mean = %.2f.\nThe mean blue intensity = %.2f.',...
redMean, greenMean, blueMean);
uiwait(helpdlg(message));
iqra Nosheen
am 21 Jan. 2021
@Image Analyst i want to ask other question , i'm working on attached image to extract subimages of handwritten alphabets , In first row there are computerized and in second row there are handwritten alphabets. i'm cropping alphabets using boundingbox property of regionprops and saving in corresponding folder. The problem is by default it is starting from left side and moving vertically,i want it should move row wise and just take 2nd,4rth,6th,8th,10th and 12th row and sholud ignore other rows. please guide me how to do so![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/495373/image.png)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/495373/image.png)
1 Kommentar
Image Analyst
am 21 Jan. 2021
You can use kmeans() to identfy the centroids rows and columns. Then assign new labels.
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