Intuitionistic fuzzy set and fuzzy mathematical morphology applied to color leukocytes segmentation

This work presents a new algorithm based on Atanassov’s intuitionistic fuzzy sets and fuzzy mathematical morphology to leukocytes segmentation in color images. The main idea is based on modeling a color image as an Atanassov’s intuitionistic fuzzy set using the hue component in the HSV color space. Then, a pixel labeled as leukocyte is selected and compared to the whole image with a similarity measure. Thus, the leukocyte is segmented and separated from the rest of the image. The experimental results show that the algorithm has a good performance, reaching a value of 99.41% for the correct classification of leukocytes and a 99.23% for the correct classification of the background. Other metrics such as accuracy, precision and recall have been calculated obtaining 99.32%, 99.41% and 99.24%, respectively. The algorithm presents two important characteristics: It works directly over the color images without the need of converting the image in gray scale, and it does not produce false colors because fuzzy morphological operators guarantee it.