what is the ideal solution to find a color in an image?

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Carole 2012-10-15

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Hi, what is the ideal solution to find a color in an image? knowing that I have used these lines with matlab but I didn't come to make clear the correct RGB values of colors. Every time I find a value for example light brown I found that: R = 173, G = 129, B = 80 and on other sites I found that: R = 181, G = 101, B = 29

idx = I(:,:,1) == ?? & I(:,:,2) == ?? & I(:,:,3) == ??;
C = any( idx(:) );

thanks

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Answer 1

Image Analyst 2012-10-15

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Guess what? They're both light brown. Did you think that light brown was only 1 of the 16 million possible colors, and not, say tens of thousands of possible values? Actually colors are a continuum and where in color space you say one color stops and the other takes over is a matter of opinion - a judgment call. What you call a color can span a range of RGB values - it's not just one single value.

You might want to look over my color segmentation tutorials: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862

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Carole 2012-10-15

编辑：Carole 2012-10-16

在 MATLAB Online 中打开

I didn't understand how I can find the mean LAB or HSV color of light brown?? I tried to do this but it's used to find LAB or HSV color of the orginal image. I hope you'll be patient because this is the first time I've worked on this kind of application. I try to implement the code step by step using your advice

rgbImage=imread('img21.png'); %the original image that i will detect the color from it
figure(1);imshow(rgbImage);
fontSize=14;
% Convert image from RGB colorspace to lab color space.
cform = makecform('srgb2lab');
lab_Image = applycform(im2double(rgbImage),cform);
  
% Extract out the color bands from the original image
% into 3 separate 2D arrays, one for each color component.
LChannel = lab_Image(:, :, 1); 
aChannel = lab_Image(:, :, 2); 
bChannel = lab_Image(:, :, 3); 
  
% Display the lab images.
figure(2);imshow(LChannel, []);
title('L Channel', 'FontSize', fontSize);
figure(3);imshow(aChannel, []);
title('a Channel', 'FontSize', fontSize);
figure(4);imshow(bChannel, []);
title('b Channel', 'FontSize', fontSize);
% Get the average lab color value.
[LMean, aMean, bMean] = GetMeanLABValues(LChannel, aChannel, bChannel)

Carole 2012-10-20

移动：DGM 2023-12-30

在 MATLAB Online 中打开

I used this image to extract mean values: LMean, aMean, bMean of light brown.

http://img15.hostingpics.net/pics/506203cork1.png

Is this correct??

[mask storedColorMap] =imread('cork1.png');
figure(1);imshow(mask);
fontSize=14;
[rows columns numberOfColorBands] = size(mask); 
  if strcmpi(class(mask), 'uint8')
    eightBit = true;
  else
    eightBit = false;
  end
  if numberOfColorBands == 1
    if isempty(storedColorMap)
      mask = cat(3, mask, mask, mask);
        else
      mask = ind2rgb(mask, storedColorMap);
      if eightBit
        mask = uint8(255 * mask);
      end
    end
  end
h1 = subplot(3, 4, 1);
  imshow(mask);
cform = makecform('srgb2lab');
lab_Image = applycform(im2double(mask),cform);
LChannel = lab_Image(:, :, 1);
aChannel = lab_Image(:, :, 2);
bChannel = lab_Image(:, :, 3);
figure(2);imshow(LChannel, []);
figure(3);imshow(aChannel, []);
figure(4);imshow(bChannel, []);
[LMean, aMean, bMean] = GetMeanLABValues(LChannel, aChannel, bChannel, mask)
[rgbImage storedColor] =imread('7.png');
figure(5);imshow(rgbImage);
fontSize=14;
[R C numberOfColorBand] = size(rgbImage);
cform = makecform('srgb2lab');
lab = applycform(im2double(rgbImage),cform);
L = lab(:, :, 1);
a = lab(:, :, 2);
b = lab(:, :, 3);
figure(6);imshow(L, []);
figure(7);imshow(a, []);
figure(8);imshow(b, []);
  LStandard = LMean * ones(R, C);
  aStandard = aMean * ones(R, C);
  bStandard = bMean * ones(R, C);
    deltaL = L - LStandard;
  deltaa = a - aStandard;
  deltab = b - bStandard;
    deltaE = sqrt(deltaL .^ 2 + deltaa .^ 2 + deltab .^ 2);
    maskedDeltaE = deltaE .* mask;
    meanMaskedDeltaE = mean(deltaE(mask));
    stDevMaskedDeltaE = std(deltaE(mask));
    message = sprintf('The mean LAB = (%.2f, %.2f, %.2f).\nThe mean Delta E in the masked region is %.2f +/- %.2f',...
    LMean, aMean, bMean, meanMaskedDeltaE, stDevMaskedDeltaE);
    imshow(maskedDeltaE, []);
  caption = sprintf('Delta E between image within masked region\nand mean color within masked region.\n(With amplified intensity)');
  title(caption, 'FontSize', fontSize);

But i had this error

??? Error using ==> mtimes
Inputs must be 2-D, or at least one input must be scalar.
To compute elementwise TIMES, use TIMES (.*) instead.
Error in ==> findcolor at 49
  LStandard = LMean * ones(R, C);

Carole 2012-10-20

移动：DGM 2023-12-30

在 MATLAB Online 中打开

Hi, Did you mean that since the image cork is uniform, I don't need the function GetMeanLABValues? I tried to do this code. Is it correct because i had this error?? How I can correct it?

??? Error using ==> times
Matrix dimensions must agree.
Error in ==> findcolor at 45
maskedDeltaE = deltaE .* mask;

The code

lab_Image = applycform(im2double(mask),cform);
LMean = lab_Image(1,1,1);
aMean = lab_Image(1,1,2);
bMean = lab_Image(1,1,3);
[rgbImage storedColor] =imread('7.png');
figure(2);imshow(rgbImage);
[R C numberOfColorBand] = size(rgbImage);
cform = makecform('srgb2lab');
lab = applycform(im2double(rgbImage),cform);
L = lab(:, :, 1);
a = lab(:, :, 2);
b = lab(:, :, 3);
figure(3);imshow(L, []);
figure(4);imshow(a, []);
figure(5);imshow(b, []);
LStandard = LMean * ones(R, C);
aStandard = aMean * ones(R, C);
bStandard = bMean * ones(R, C);
deltaL = L - LStandard;
deltaa = a - aStandard;
deltab = b - bStandard;
deltaE = sqrt(deltaL .^ 2 + deltaa .^ 2 + deltab .^ 2);
mask=double(mask);
maskedDeltaE = deltaE .* mask;
meanMaskedDeltaE = mean(deltaE(mask));
stDevMaskedDeltaE = std(deltaE(mask));
figure(6);imshow(maskedDeltaE, []);
figure(7);imshow(deltaE, []);
numberOfLines = 1;
strTolerance = sprintf('%.1f', meanMaskedDeltaE + 3 * stDevMaskedDeltaE);
defaultAnswer = {strTolerance};
response = inputdlg(prompt, dialogTitle, numberOfLines, defaultAnswer);
tolerance = str2double(cell2mat(response));

Carole 2012-10-21

移动：DGM 2023-12-30

在 MATLAB Online 中打开

mask is the image cork1. This is the code:

[mask storedColorMap] =imread('cork1.png');
figure(1);imshow(mask);
fontSize=14;
[rows columns numberOfColorBands] = size(mask); 
  if strcmpi(class(mask), 'uint8')
    eightBit = true;
  else
    eightBit = false;
  end
  if numberOfColorBands == 1
    if isempty(storedColorMap)
      mask = cat(3, mask, mask, mask);
        else
      mask = ind2rgb(mask, storedColorMap);
      if eightBit
        mask = uint8(255 * mask);
      end
    end
  end
cform = makecform('srgb2lab');
lab_Image = applycform(im2double(mask),cform);
LMean = lab_Image(1,1,1);
aMean = lab_Image(1,1,2);
bMean = lab_Image(1,1,3);
[rgbImage storedColor] =imread('7.png');
figure(2);imshow(rgbImage);
[R C numberOfColorBand] = size(rgbImage);
cform = makecform('srgb2lab');
lab = applycform(im2double(rgbImage),cform);
L = lab(:, :, 1);
a = lab(:, :, 2);
b = lab(:, :, 3);
figure(3);imshow(L, []);
figure(4);imshow(a, []);
figure(5);imshow(b, []);
LStandard = LMean * ones(R, C);
aStandard = aMean * ones(R, C);
bStandard = bMean * ones(R, C);
deltaL = L - LStandard;
deltaa = a - aStandard;
deltab = b - bStandard;
deltaE = sqrt(deltaL .^ 2 + deltaa .^ 2 + deltab .^ 2);
mask=double(mask);
maskedDeltaE = deltaE .* mask;
meanMaskedDeltaE = mean(deltaE(mask));
stDevMaskedDeltaE = std(deltaE(mask));
figure(6);imshow(maskedDeltaE, []);
figure(7);imshow(deltaE, []);
numberOfLines = 1;
strTolerance = sprintf('%.1f', meanMaskedDeltaE + 3 * stDevMaskedDeltaE);
defaultAnswer = {strTolerance};
response = inputdlg(prompt, dialogTitle, numberOfLines, defaultAnswer);
tolerance = str2double(cell2mat(response));

But i had this error

??? Error using ==> mtimes
Inputs must be 2-D, or at least one input must be scalar.
To compute elementwise TIMES, use TIMES (.*) instead.
Error in ==> findcolor at 49
  LStandard = LMean * ones(R, C);

Image Analyst 2012-10-22

移动：DGM 2023-12-30

在 MATLAB Online 中打开

I don't think you really understand what's going on. You don't understand what a mask is, what a reference color is, and probably a lot of other stuff. Look over this demo and try to understand what I did. It is well commented. Make sure you change the folder and filenames to what they are on your computer.

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.
format longg;
format compact;
fontSize = 12;
folder = 'C:\Users\Carole\Documents\Temporary';
uniformFileName = fullfile(folder, '506203cork1.png');
rgbUniformImage =imread(uniformFileName);
[rows columns numberOfColorBands] = size(rgbUniformImage);
subplot(3, 4, 1);
imshow(rgbUniformImage);
title('Reference Color Uniform Image', 'FontSize', fontSize);
corkFileName = fullfile(folder, '658945img21.png');
rgbCorkImage =imread(corkFileName);
[rows2 columns2 numberOfColorBands2] = size(rgbCorkImage);
subplot(3, 4, 2);
imshow(rgbCorkImage);
title('Cork Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
cform = makecform('srgb2lab');
% Get lab versions.
lab_ImageUniform = applycform(im2double(rgbUniformImage),cform);
lab_ImageCork = applycform(im2double(rgbCorkImage),cform);
% Get the lab value of the reference uniform image.
L_reference = lab_ImageUniform(1,1, 1);
A_reference = lab_ImageUniform(1,1, 2);
B_reference = lab_ImageUniform(1,1, 3);
message = sprintf('The mean LAB of the reference = (%.2f, %.2f, %.2f).\n',...
  L_reference, A_reference, B_reference);
uiwait(msgbox(message));
% Get the delta E between the ref color and the sample image.
deltaL = lab_ImageCork(:, :, 1) - L_reference;
deltaA = lab_ImageCork(:, :, 2) - A_reference;
deltaB = lab_ImageCork(:, :, 3) - B_reference;
% Show them all
subplot(3, 4, 3);
imshow(deltaL, []);
title('Delta L Image', 'FontSize', fontSize);
subplot(3, 4, 4);
imshow(deltaA, []);
title('Delta A Image', 'FontSize', fontSize);
subplot(3, 4, 5);
imshow(deltaB, []);
title('Delta B Image', 'FontSize', fontSize);
% Get the delta E between the ref color and the sample image.
deltaE = sqrt(deltaL.^2 + deltaA.^2 + deltaB.^2);
subplot(3, 4, 6);
imshow(deltaE, []);
title('Delta E Image', 'FontSize', fontSize);
% Get a histogram of the deltaE image
[counts values] = hist(deltaE(:), 64);
subplot(3, 4, 9:12);
bar(values, counts, 1);
title('Histogram of the Delta E Image', 'FontSize', fontSize);
grid on;
% Threshold the deltaE image to get low delta Es.
deltaEthreshold = 44;
binaryImage = deltaE < deltaEthreshold;
subplot(3, 4, 7);
imshow(binaryImage, []);
caption = sprintf('Delta Es < %d', deltaEthreshold);
title(caption, 'FontSize', fontSize);
% Get a masked image
% Mask the image.
maskedRgbImage = bsxfun(@times, rgbCorkImage, cast(binaryImage,class(rgbCorkImage)));
subplot(3, 4, 8);
imshow(maskedRgbImage, []);
title('Masked Delta E Image', 'FontSize', fontSize);

Pamela Paolo 2012-11-3

移动：DGM 2023-12-30

在 MATLAB Online 中打开

To find a specific color (blue-grey) in an image we can't use:

idx = I(:,:,1) == ?? & I(:,:,2) == ?? & I(:,:,3) == ??;
C = any( idx(:) );

Because every color has many R, G and B values. So how i can find this color without using a uniform image?

Image Analyst 2012-11-4

移动：DGM 2023-12-30

Right. And I know you've seen my color classification tutorials in my File Exchange, so......why can't you use one of them? What colors you get around blue-gray depends on what method you use. The delta E mathod carves out a sphere out of the gamut in LAB space, while the HSV method carves out a sector in HSV space. So, while similar, they may get different colors out near the extremes of the range you're extracting.

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Answer 2

Pamela Paolo 2012-11-5

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The delta E method allows the user to pick a color as an example from the image and then it will find all the other pixels with similar color to that in the image while this isn't the case in my project. The code should allow to find a specific color from the beginning (blue-grey) without user intervention. As you said, to adapt this code to our situation, we can use it to find the mean LAB or HSV color of blue-grey. How? What is the image used to find this mean Lab or HSV color of blue-grey?

This code <https://www.mathworks.com/matlabcentral/fileexchange/28512-simple-color-detection-by-hue/content/SimpleColorDetectionByHue.m> detect yellow regions using a given low and high thresholds. In my case i don't have the low and high thresholds of blue-grey. How can I do this?

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Image Analyst 2012-11-6

移动：DGM 2023-12-30

I do understand your question. I know you don't know the values - yet - that's why I said " just look at the h, s, and v values at some particular pixel location that has a blue-gray pixel to discover what the h, s, and v values actually are". Then you know what the values are, then you hard code it into your program. Why will that not work?

Image Analyst 2012-11-15

移动：DGM 2023-12-30

Pick your color values from one of these web sites:

http://en.wikipedia.org/wiki/List_of_colors

http://www.w3.org/TR/css3-color/

http://ivrg.epfl.ch/files/content/sites/ivrg/files/research/alindner/CIC2012/www/ColorThesaurus.html Type blue-grey (using the UK spelling of gray) into the search field. You can type any color in any language in and get the color. Or, pick a color from a color picker and find out the names in 9 or 10 different languages for that color.

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what is the ideal solution to find a color in an image?

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what is the ideal solution to find a color in an image?

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