pen(binary_mask, 50); % Fill holes filled_mask = imfill(clean_mask, 'holes'); % Display refined segmentation figure; imshow(filled_mask); title('Refined Segmentation'); ``` Advanced Thresholding Techniques and Customizat
end wF = total - wB; if wF == 0 break; end sumB = sumB + (t-1)counts(t); mB = sumB / wB; mF = (sum1 - sumB) / wF; % Calculate between class variance between = wB wF (mB - mF)^2; if between > maximum maximum = between; threshold = (t-1)/255; end end end ``` This function calculates the optimal th
e figure; imshow(binaryImg); title('Manual Adaptive Thresholding using Local Mean'); ``` Note: This manual method is less efficient for large images but illustrates the core concept. Optimizing Adaptive Thresholding in MATLAB Parameter Tuning Sensitivi
