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Hello,

how can I decide that an image is symmetric or asymmetric in color after dividing it into two parts vertically (the right part and the left part)? thanks

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Answer by Image Analyst
on 8 Nov 2012

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You could chop the image in half, call fliplr() to flip one of the halves, then check similarity with SSIM (See wikipedia) or something similar like PSNR.

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I used fliplr() but i get this error

??? Error using ==> fliplr at 18 X must be a 2-D matrix.

Error in ==> code at 40 B = fliplr(A);

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Then you have to extract each color channel

% Extract the individual red, green, and blue color channels. redChannel = rgbImage(:, :, 1); greenChannel = rgbImage(:, :, 2); blueChannel = rgbImage(:, :, 3);

and flip them one at a time, then recombine:

rgbImage = cat(3, redChannel, greenChannel, blueChannel);

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I used this function of SSIM

function [mssim, ssim_map] = ssim_index(img1, img2, K, window, L) if (nargin < 2 || nargin > 5) ssim_index = -Inf; ssim_map = -Inf; return; end

if (size(img1) ~= size(img2)) ssim_index = -Inf; ssim_map = -Inf; return; end

[M N] = size(img1);

if (nargin == 2) if ((M < 11) || (N < 11)) ssim_index = -Inf; ssim_map = -Inf; return end %window = fspecial('gaussian', 11, 1.5); % % K(1) = 0.01; % default settings % K(2) = 0.03; % % L = 255; % end

if (nargin == 3) if ((M < 11) || (N < 11)) ssim_index = -Inf; ssim_map = -Inf; return end window = fspecial('gaussian', 11, 1.5); L = 255; if (length(K) == 2) if (K(1) < 0 || K(2) < 0) ssim_index = -Inf; ssim_map = -Inf; return; end else ssim_index = -Inf; ssim_map = -Inf; return; end end

if (nargin == 4) [H W] = size(window); if ((H*W) < 4 || (H > M) || (W > N)) ssim_index = -Inf; ssim_map = -Inf; return end L = 255; if (length(K) == 2) if (K(1) < 0 || K(2) < 0) ssim_index = -Inf; ssim_map = -Inf; return; end else ssim_index = -Inf; ssim_map = -Inf; return; end end

if (nargin == 5) [H W] = size(window); if ((H*W) < 4 || (H > M) || (W > N)) ssim_index = -Inf; ssim_map = -Inf; return end if (length(K) == 2) if (K(1) < 0 || K(2) < 0) ssim_index = -Inf; ssim_map = -Inf; return; end else ssim_index = -Inf; ssim_map = -Inf; return; end end

C1 = (K(1)*L)^2; C2 = (K(2)*L)^2; window = window/sum(sum(window)); img1 = double(img1); img2 = double(img2);

mu1 = filter2(window, img1, 'valid'); mu2 = filter2(window, img2, 'valid'); mu1_sq = mu1.*mu1; mu2_sq = mu2.*mu2; mu1_mu2 = mu1.*mu2; sigma1_sq = filter2(window, img1.*img1, 'valid') - mu1_sq; sigma2_sq = filter2(window, img2.*img2, 'valid') - mu2_sq; sigma12 = filter2(window, img1.*img2, 'valid') - mu1_mu2;

if (C1 > 0 && C2 > 0) ssim_map = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))./((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2)); else numerator1 = 2*mu1_mu2 + C1; numerator2 = 2*sigma12 + C2; denominator1 = mu1_sq + mu2_sq + C1; denominator2 = sigma1_sq + sigma2_sq + C2; ssim_map = ones(size(mu1)); index = (denominator1.*denominator2 > 0); ssim_map(index) = (numerator1(index).*numerator2(index))./(denominator1(index).*denominator2(index)); index = (denominator1 ~= 0) & (denominator2 == 0); ssim_map(index) = numerator1(index)./denominator1(index); end %figure,imshow(ssim_map); mssim = mean2(ssim_map); %figure,imshow(mat2gray(ssim_map)) return

but i get this error

??? Undefined function or method 'conv2' for input arguments of type 'double' and attributes 'full 3d real'.

Error in ==> filter2 at 73 y = conv2(hcol, hrow, x, shape);

Error in ==> ssim_index at 136 mu1 = filter2(window, img1, 'valid');

Error in ==> ssim at 7 [mssim, ssim_map] = ssim_index(img1, img2, K, window, L)

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I want to find the score of asymmetry in color so I don't know what should I use rgb or hsv

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Hello

function [mssim, ssim_map] = ssim_index(img1, img2, K, window, L) if (nargin < 2 || nargin > 5) ssim_index = -Inf; ssim_map = -Inf; return; end if (size(img1) ~= size(img2)) ssim_index = -Inf; ssim_map = -Inf; return; end [M N] = size(img1); if (nargin == 2) if ((M < 11) || (N < 11)) ssim_index = -Inf; ssim_map = -Inf; return end %window = fspecial('gaussian', 11, 1.5); % % K(1) = 0.01; % default settings % K(2) = 0.03; % % L = 255; % end if (nargin == 3) if ((M < 11) || (N < 11)) ssim_index = -Inf; ssim_map = -Inf; return end window = fspecial('gaussian', 11, 1.5); L = 255; if (length(K) == 2) if (K(1) < 0 || K(2) < 0) ssim_index = -Inf; ssim_map = -Inf; return; end else ssim_index = -Inf; ssim_map = -Inf; return; end end if (nargin == 4) [H W] = size(window); if ((H*W) < 4 || (H > M) || (W > N)) ssim_index = -Inf; ssim_map = -Inf; return end L = 255; if (length(K) == 2) if (K(1) < 0 || K(2) < 0) ssim_index = -Inf; ssim_map = -Inf; return; end else ssim_index = -Inf; ssim_map = -Inf; return; end end if (nargin == 5) [H W] = size(window); if ((H*W) < 4 || (H > M) || (W > N)) ssim_index = -Inf; ssim_map = -Inf; return end if (length(K) == 2) if (K(1) < 0 || K(2) < 0) ssim_index = -Inf; ssim_map = -Inf; return; end else ssim_index = -Inf; ssim_map = -Inf; return; end end C1 = (K(1)*L)^2; C2 = (K(2)*L)^2; window = window/sum(sum(window)); img1 = double(img1); img2 = double(img2); mu1 = filter2(window, img1, 'valid'); mu2 = filter2(window, img2, 'valid'); mu1_sq = mu1.*mu1; mu2_sq = mu2.*mu2; mu1_mu2 = mu1.*mu2; sigma1_sq = filter2(window, img1.*img1, 'valid') - mu1_sq; sigma2_sq = filter2(window, img2.*img2, 'valid') - mu2_sq; sigma12 = filter2(window, img1.*img2, 'valid') - mu1_mu2; if (C1 > 0 && C2 > 0) ssim_map = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))./((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2)); else numerator1 = 2*mu1_mu2 + C1; numerator2 = 2*sigma12 + C2; denominator1 = mu1_sq + mu2_sq + C1; denominator2 = sigma1_sq + sigma2_sq + C2; ssim_map = ones(size(mu1)); index = (denominator1.*denominator2 > 0); ssim_map(index) = (numerator1(index).*numerator2(index))./(denominator1(index).*denominator2(index)); index = (denominator1 ~= 0) & (denominator2 == 0); ssim_map(index) = numerator1(index)./denominator1(index); end %figure,imshow(ssim_map); mssim = mean2(ssim_map); %figure,imshow(mat2gray(ssim_map)) return

This method can help me to measure the asymmetry index of a color region of interest?? knowing that the background is black. I have now two images, after dividing the segmented image, each containing a portion of the region although divided along the major axis. So how can I adapt this method to my need??

thanks

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ssim can help me?? knowing that I have a color image. I need your help please

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Where did you post examples of your symmetric and non-symmetric images?

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I'm working on a large number of images with different colors. I want to calculate the score of asymmetry in color, texture and shape.

Examples of images after a segmentation step:

symmetric http://s11.postimage.org/5t2rws3/tachymmetric.jpg

asymmetric http://s9.postimage.org/xorjshb/tachsymmetric.jpg

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Hey Pamela,

I think you are working through melanoma diagnosis applying (ABCD rule), am working through the same target, where i am trying to calculate asymmetry score in color and texture for a segmented image... did you reach an effective method??!

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**I did** , sort of - did you see the **link** I gave you? That will have the best methods by people who have studied it intensively. Maybe my *guess* of SSIM is not even the best way.

If you still want ssim(), upgrade to the latest version of MATLAB, or program it yourself with information from http://en.wikipedia.org/wiki/Structural_similarity

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