OTSU分割
function main_script()clc;
addpath('./implementation')
result_matrix = zeros(10,6);
threshold_matrix = zeros(10,6);
for i = 0 : 9
I = imread(['./data/sample' num2str(i) '.tif']);
h = entropy_otsu(I);
result_matrix(i+1,1) = pixel_count(I, h);
threshold_matrix(i+1,1) = h;
h = my_otsu(I);
result_matrix(i+1,2) = pixel_count(I, h);
threshold_matrix(i+1,2) = h;
h = valley_emphasis(I);
result_matrix(i+1,3) = pixel_count(I, h);
threshold_matrix(i+1,3) = h;
h = neighbor_valley_emphasis(I,5);
result_matrix(i+1,4) = pixel_count(I, h);
threshold_matrix(i+1,4) = h;
h = gaussian_valley_emphasis(I,5);
result_matrix(i+1,5) = pixel_count(I, h);
threshold_matrix(i+1,5) = h;
h = lda_valley_emphasis(I);
result_matrix(i+1,6) = pixel_count(I, h);
threshold_matrix(i+1,6) = h;
end
fprintf('Table 1. Pixel counts of defect regions.\n')
fprintf()
fprintf('Image # Proposed methodValley-emphasisNeighbor-VEFisher''s LDA\n');
fprintf()
for i = 1 : 10
fprintf([num2str(i) '\t' ...
num2str(result_matrix(i,1)) '\t\t ' ...
num2str(result_matrix(i,3)) '\t\t ' ...
num2str(result_matrix(i,4)) '\t\t ' ...
num2str(result_matrix(i,6)) '\n']);
end
fprintf()
fprintf('Table 2. Output thresholds.\n')
fprintf()
fprintf('Image # Proposed methodValley-emphasisNeighbor-VEFisher''s LDA\n');
fprintf()
for i = 1 : 10
fprintf([num2str(i) '\t' ...
num2str(threshold_matrix(i,1)) '\t\t ' ...
num2str(threshold_matrix(i,3)) '\t\t ' ...
num2str(threshold_matrix(i,4)) '\t\t ' ...
num2str(threshold_matrix(i,6)) '\n']);
end
fprintf()
rmpath('./implementation')
end
function output = pixel_count( img, threshold )
img = im2bw(img, threshold/255);
% if the thresholded image is mainly black, white pixels are supposed
% to be abnormal, and vice versa
if sum(sum(img == 0)) > sum(sum(img == 1))
output =sum(sum(img == 1));
else
output =sum(sum(img == 0));
end
end
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