applying thresholds simultaneously in SimpleColorDetectionByHue()

3 次查看（过去 30 天）

giacomo 2017-9-20

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/357599-applying-thresholds-simultaneously-in-simplecolordetectionbyhue

评论： Image Analyst 2019-3-25

I'm trying to use this program to detect not one but three different colors (red green blue) at the same time, applying three different thresholds. Is there a way? Try to explain each little step because I haven't used Matlab for a while and I'm a bit rusty. Thank you all!

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Image Analyst 2017-9-20

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/357599-applying-thresholds-simultaneously-in-simplecolordetectionbyhue#answer_282431

编辑：Image Analyst 2017-9-20

在 MATLAB Online 中打开

Yes, basically just do each color one at a time and get a mask for each one, then OR them together.

% Set hsv thresholds for color1
maskColor1 = ........  % Create mask based on those thresholds.
% Set hsv thresholds for color2
maskColor2 = ........
% Set hsv thresholds for color3
maskColor3 = ........
% Get the mask for all 3
allThreeColorsMask = maskColor1  | maskColor2 | maskColor3;

17 个评论
显示 15更早的评论隐藏 15更早的评论

giacomo 2017-9-26

编辑：giacomo 2017-9-29

在 MATLAB Online 中打开

Thanks. I used that app and it worked really good. Kinda though, since if I select only the green and blue part it works and gives me good results, but if I select also the red one (or only the red one) it gives me wrong results (red part is basically pitch black). I did the 'OR them together' mask and I also looked at your suggestion in the code saying I should create two hue masks for red to catch every kind of red, but still doesn't work. I'm almost certain I did everything I could. I paste here the script of those passages:

Thresholds

    %%%%%%
%Red
                        hueThresholdLowR1 = 0.8;
      hueThresholdHighR1 = 1;
                        hueThresholdLowR2 = 0;
      hueThresholdHighR2 = 0.1;
      saturationThresholdLowR = 0.6;
      saturationThresholdHighR = 1;
      valueThresholdLowR = 0.55;
      valueThresholdHighR = 1;

Hue mask for red

%red
  hueMaskR1 = (hImage >= hueThresholdLowR1) & (hImage <= hueThresholdHighR1);
  hueMaskR2 = (hImage >= hueThresholdLowR2) & (hImage <= hueThresholdHighR2);
  hueMaskR = hueMaskR1 & hueMaskR2;
  saturationMaskR = (sImage >= saturationThresholdLowR) & (sImage <= saturationThresholdHighR);
  valueMaskR = (vImage >= valueThresholdLowR) & (vImage <= valueThresholdHighR);

(then regular masks for the other two colors) and combine them

    %%%%%%%%%%%%%
    %combine the three masks for the three colors in a unique mask
    hueMask = hueMaskR | hueMaskG | hueMaskB;
    saturationMask = saturationMaskR | saturationMaskG | saturationMaskB;
    valueMask = valueMaskR | valueMaskG | valueMaskB;

Let me know what I'm doing wrong Cheers

giacomo 2017-10-16

在 MATLAB Online 中打开

Done! One more question. What about if I want to evaluate the porosity in 4 areas of the cropped image? Would it be something like:

    % 
  
hsvImage = rgb2hsv(rgbImage);
[r, c, p] = size(hsvImage); 
DarkAreas1 = vImage(1:r,1:c/4,:);
Porosity1 = sum(darkAreas1(:))/numel(darkAreas);

same thing for the other three areas and then mean for the total porosity? (it's to display the heterogeneity of the index from top to bottom of the image). Then I wanted to load another image after the elements have been stressed to evaluate the same index and a global one for comparison. The important thing is that the cropped area has to be the same in coordinates and width/height (pic position will be the same since it's same camera and same position of shooting). It has something to do with 'rect' command but I'm not sure what. Thank you. Please tell me if I should create another question for this. :)

Image Analyst 2017-10-17

在 MATLAB Online 中打开

Not sure what you want, but what you are doing is taking the leftmost quarter strip of the image, and getting the mean all the gray levels in that vertical strip. The last two lines could be done like this:

Porosity1 = mean2(vImage(1:r,1:c/4,:));

Of course you need to define vImage. Did you mean hsvImage? Or did you mean (but left out)

vImage = hsvImage(:, :, 1); % Extract value channel.

If you meant that, then you can leave off the final colon:

Porosity1 = mean2(vImage(1:r,1:c/4));

If you want a fixed number of columns, instead of 1/4 the width of the image, then just specify it. For example, use 100 instead of c/4. It does not need to involve rect() unless you want the user to be able to adjust the location of the box interactively over the image.

请先登录，再进行评论。