MATLAB: Using post classification confusion matrix

confusion matriximage processingMATLABpost-classification

Pls I need to perform confusion matrix, but I keep getting;
Error using confusion (line 43)
Targets and outputs have different dimensions.
The code I used is;
[c,cm,ind,per] = confusion(BW_1,new_image{1})
where;
BW_1=roipoly(my_image); %Trained class no. 1
BW_1 gives a (2592×4608 logical) variable value in the Workspace part
<2592x4608 logical>
new_image
new_image =
Columns 1 through 4
    [7776x4608 uint8]    [7776x4608 uint8]    [7776x4608 uint8]    [7776x4608 uint8]
Columns 5 through 6
    [7776x4608 uint8]    [7776x4608 uint8]
Kmeans Segmentation code used
he= imread('C:\Users\ISHOLA\Desktop\1.jpg'); %Reading image which is not gray
  cform = makecform('srgb2lab');
  lab_he = applycform(he,cform);
  ab = double(lab_he(:,:,2:3));
  nrows = size(ab,1);
  ncols = size(ab,2);
  disp(nrows);
  disp(ncols);
  ab = reshape(ab,nrows*ncols,2);
  nColors = 6;
  % repeat the clustering 3 times to avoid local minima
  [cluster_idx cluster_center] = kmeans(ab,nColors,'distance','sqEuclidean','replicates',6);
  pixel_labels = reshape(cluster_idx,nrows,ncols);
  %figure, imshow(pixel_labels,[]), title('image labeled by cluster index');
  segmented_images = cell(1,3);
  rgb_label = repmat(pixel_labels,[1 3]);
    for k = 1:nColors
        color = he;
        color(rgb_label ~= k) = 0;
        segmented_images{k} = color;
    end
    new_image = cellfun(@(x)reshape(x,2592*3,4608),segmented_images,'UniformOutput',false)

Best Answer

Well, the answer is right in front of you. BW_1 has 2592x4608=11943936 elements while new_image{1} has 7776x4608=35831808 elements
confusion requires both of them have same number of elements.
since 7776/2592=3, it is possible that you made some mistake and all 3 color bands are getting next to each other on first dimension.If your image looks black and white, it is still possible that it has three color bands; but the colors are set in such a way that it looks gray.
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