Image processing using knn

I have 3 images that I have to label using the knn algorithm and another 18 images that i know. I don't know how to label those 18 img using a variable 18x1 named etichete and don't know how to classificate them using the knn. ext_auto is the function for maximum contrast extension. And it doesn't show hist1,hist2, hist3.

• maximum contrast extension, adaptive variant
• histogram calculation
• patient identification using the algorithm for classifying the closest k-neighbors (k-nearest neighbor - knn), the comparison will be made at the histogram level.

img1 = imread('img34.png');
img2 = imread('img35.png');
img3 = imread('img36.png');
img1 = ext_auto(img1,1);
img2 = ext_auto(img2,1);
img3 = ext_auto(img3,1);
hist1 = histogram(img1,'Normalization','probability');
hist2 = histogram(img2,'Normalization','probability');
hist3 = histogram(img3,'Normalization','probability');
figure,
subplot(2,3,1), imshow(hist1);
subplot(2,3,2), imshow(hist2);
subplot(2,3,3), imshow(hist3);

locatie = 'C:\Users\User\Desktop\Facultate\Anul III\Semestrul II\tsim\Tema2\antrenare';       
files=dir(fullfile(locatie, '*.png'));
load('etichete.mat');
h = zeros(length(files),256);
for i = 1:length(files)
    FileName = fullfile(locatie, files(i).name);
    img = imread(FileName);
    img = ext_auto(img,1);
    hist = histogram(img,'Normalization','probability');
    figure(i),  imhist(img);
end

Answer 1

[Image Analyst]

You can't use imshow on a histogram object. You need to use plot() or bar():

counts = hist1.Values;
binCenters = (hist1.BinEdges(1:end-1) + hist1.BinEdges(2:end)) / 2;
bar(binCenters, counts);
xlabel('Gray Level', 'FontSize', 15);
ylabel('Counts', 'FontSize', 15);

Warning: If your image is RGB, the counts are of all the gray levels, regardless of what color channel they're in!