find spatial coordinates (x,y) for a pixel value in color image? (Opposite of impixel function)

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Tanmoy 2015-5-20

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/217661-find-spatial-coordinates-x-y-for-a-pixel-value-in-color-image-opposite-of-impixel-function

评论： Walter Roberson 2015-5-31

I have a color image with 2 circle (one with red, one with blue i.e. I know the pixel value of these two component). I need to extract (x,y) coordinates of the areas covered by this two color. The opposite is done by IMPIXEL function e.g. for a known (x,y), impixel will give us PIXEL value of that location. But, in my case, I need (n*2) matrix of (x,y) spatial coordinates of known pixel values (the colored components). Any suggestion?

I am thinking about

1.

conn_c = bwconncomp(colored_image);  
PixelListTo  = regionprops(conn_c,'PixelList');

I did that for binary image. In current case, I need to input two different color which is not possible in bwconncomp.

2. IMPROFILE will give me (x,y) for defined endpoints of line segment, is there any way to put pixel value so that (x,y) coordinate for that pixel value (can be multiple points) can be obtained.

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Tanmoy 2015-5-29

编辑：Tanmoy 2015-5-31

Example of color component

Tanmoy 2015-5-29

But actually, for example, in the attached color file,

I need to find all (x,y) coordinates of a component as (n*2) matrix (n = number of pixel points with similar color). Each connected component in the image have separate color (e.g. RGB = 255,0,50 for 1st component, RGB = 255, 0,100 for 2nd component).

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Answer 1

Walter Roberson 2015-5-20

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链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/217661-find-spatial-coordinates-x-y-for-a-pixel-value-in-color-image-opposite-of-impixel-function#answer_179733

在 MATLAB Online 中打开

   R = colored_image(:,:,1);
   G = colored_image(:,:,2);
   B = colored_image(:,:,3);
   matches1 = R == target1R & G == target1G & B == target1B;
   matches2 = R == target2R & G == target2G & B == target2B;

now you can run bwconncomp on matches1 and matches2.

If you only have one circle of each color, then you could potentially skip bwconncomp and regionprops PixelIdList and just use

[x1, y1] = find(matches1);
[x2, y2] = find(matches2);

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Walter Roberson 2015-5-20

编辑：Walter Roberson 2015-5-20

在 MATLAB Online 中打开

target1R is the red component of the first kind of pixel you want to match. target1G is the green component of the first kind of pixel you want to match. and so on.

When you are trying to find pixels then in general you need to match all three components, the red, green, and blue.

In the particular case where you know that your image divides perfectly by color component, that a pixel that has the right red component will never have a non-zero blue or green component, then you can simplify the search. Using RedValueToMatch to represent the red pixel component value you want to match, and BlueValueToMatch to represent the blue pixel component value you want to match, under these conditions (which never apply for standard JPEG files!)

Example:

%change the two values according to your situation
RedValueToMatch = 240;   %the red circle was drawn with (240,0,0)
BlueValueToMatch = 133;  %the blue circle was drawn with (0,0,133)
matches1 = colored_image(:,:,1) == RedValueToMatch;
matches2 = colored_image(:,:,2) == BlueValueToMatch;
conn_c1 = bwconncomp(matches1);  
PixelListTo1  = regionprops(conn_c1,'PixelList');
conn_c2 = bwconncomp(matches2);  
PixelListTo2  = regionprops(conn_c2,'PixelList');

Tanmoy 2015-5-31

编辑：Tanmoy 2015-5-31

I know the color values (e.g. [136 0 21], [0 162 232], [255 201 14]), so, for my code, input is these 3 vector, I need (x,y) coordinates for each color. Something that works as reverse of IMPIXEL function!

Walter Roberson 2015-5-31

在 MATLAB Online 中打开

colored_image = imread('Tammoy217661.png');
target1R = 136; target1G = 0; target1B = 21;
target2R = 0; target2G = 162; target2B = 232;
target3R = 255; target3G = 201; target3B = 14;
R = colored_image(:,:,1);
G = colored_image(:,:,2);
B = colored_image(:,:,3);
matches1 = R == target1R & G == target1G & B == target1B;
matches2 = R == target2R & G == target2G & B == target2B;
matches3 = R == target3R & G == target3G & B == target3B;
figure; image(matches1); colormap(gray(2));
figure; image(matches2); colormap(gray(2));
figure; image(matches3); colormap(gray(2));
[r1, c1] = find(matches1);
[r2, c2] = find(matches2);
[r3, c3] = find(matches3);

This can clearly be made shorter and put into a function that searches for a particular color.

There are also numerous other ways of implementing it. For example,

locs1R = find(R == target1R);
locs1G = find(G(locs1R) == target1G);
locs1GO = locs1R(locs1G);
locs1B = find(B(locs1GO) == target1B);
locs1idx = locs1GO(locs1B);
[r1, c1] = ind2sub(size(R),locs1idx);

This might be more efficient when there are relatively few pixels of the given target, as it can end up doing few comparisons, but when the majority of locations match then it would be slower.

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